Transcript
COMPUTER-AIDED
PROCESS PLANNING (CAPP)
SECOND EDITION
SEPTEMBER 1991
ARCHITECTURE
TECHNOLOGY
CORPORATION
SPECIALISTS IN COMPUTER ARCHITECTURE
P.O. BOX 24344 · MINNEAPOLIS. MINNESOTA 55424 · (612) 935-2035
ELSEVIER
ADVANCED
TECHNOLOGY
DISTRIBUTED OUTSIDE THE USA/CANADA BY:
ELSEVIER ADVANCED TECHNOLOGY
MAYFIELD HOUSE
256 BANBURY ROAD
OXFORD
OX2 7DH
UNITED KINGDOM
® Copyright 1991 Architecture Technology Corporation. All rights reserved. No part of this publication may be reproduced, photocopied, stored on a
retrieval system, or transmitted without the express prior written consent of the publisher.
COMPUTER-AIDED
PROCESS PLANNING (CAPP)
SECOND EDITION
SEPTEMBER 1991
ARCHITECTURE
TECHNOLOGY
CORPORATION
SPECIALISTS IN COMPUTER ARCHITECTURE
P.O. BOX 24344 · MINNEAPOLIS. MINNESOTA 55424 · (612) 935-2035
ELSEVIER
ADVANCED
TECHNOLOGY
DISTRIBUTED OUTSIDE THE USA/CANADA BY:
ELSEVIER ADVANCED TECHNOLOGY
MAYFIELD HOUSE
256 BANBURY ROAD
OXFORD
OX2 7DH
UNITED KINGDOM
® Copyright 1991 Architecture Technology Corporation. All rights reserved. No part of this publication may be reproduced, photocopied, stored on a
retrieval system, or transmitted without the express prior written consent of the publisher.
DISCLAIMER
Architecture Technology Corporation makes no representations or warranties with respect to the contents
hereof and specifically disclaims any implied warranties of merchantability of fitness for any particular
purpose.
Further, reasonable care has been taken to ensure the accuracy of this report, but errors and omissions
could have occurred. Architecture Technology assumes no responsibility for any incidental or consequential damages caused thereby.
Further, Architecture Technology Corporation reserves the right to revise this guide and to make changes
from time to time in the content thereof without obligation to notify any person or organization of such
revision or changes.
This disclaimer applies to all parts of this document.
FOREWORD
Process planning involves creating detailed plans of the manufacturing steps and equipment necessary to
produce a finished part.
Workpiece requirements call for detailed analyses and accurate descriptions prior to the actual manufacturing
process. A large assortment of machines and operations, as well as many different workers with a variety of
skills, may be involved in the production of a specific part.
The computer is a vital part of the process planning function, which includes two different approaches. O n e
is called t h e variant (similar part) method of process planning and the other is generative (expert systembased). Both will produce similar process plans. Most computer applications, however, are of the variant type,
because the software is easier to develop and new process plans are based o n previous ones.
T h e variant method had its beginnings with the G T concept, along with parts classification and coding systems.
G T is a manufacturing philosophy based on the idea that similarities occur in the design and manufacture of
component parts. These parts can be classified into groups, or families, if the basic configurations and
attributes are identified. A reduction in expenses can b e achieved through the structured classification and
grouping of parts into families based upon engineering design and manufacturing similarities.
Using the variant method, C A P P groups families of parts by a structured classification and coding plan. All
previously processed parts are coded using this method. T h e parts are then divided into part families, such
as cylindrical or prismatic, based on general configuration. A standard order of operations or sequences is
stored on the computer for each part family. W h e n a new part is ready for planning, the classification or G T
code for the new part is used to compare and retrieve the standard process plan for that part family. Editing
capabilities further enable the process planner to alter the standard order of operations for final refinement.
T h e completed process plan is then stored on the computer database by part number.
In generative process planning, the parts are again broken into part families, and a detailed analysis is made
for each part family to determine individual part operations. This type of system develops the actual operation
sequence based o n the part geometry, usage requirements, material size and configuration, and available
equipment. T h e generative approach creates process planning logic for the part family groupings. The logic
is then stored internally as a decision model. As new workpieces require process planning, analyses must be
conducted to determine and compare the features incorporated in the decision model with those on the actual
part. T h e family part decision model is then retrieved, and a routing sheet is generated by processing the
decision model with t h e new workpiece attributes.
A generative system must b e driven by much m o r e elaborate and powerful software than a variant system.
Development and optimization work continues on the variant and generative approaches to process planning.
Both systems, however, build the needed decision-making logic and planning ability into the computer rather
than rely o n a decreasing experience level in the process planning work force.
Computer-Aided Process P l a n n i n g (CAPP)
Figure List
Figure 1: Production of a Simple Part
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Figure 2: Operations Overview 5
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Figure 3: Part Family Matrix File
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Figure 4: Process Plan
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Figure 5: Standard Plan Structure
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Figure 6: Basic System M e n u and Sub-program M e n u
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Figure 7: Outline of an In-house Classification and Coding System
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Figure 8: Structure of Variant Module
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Figure 9: Structure of the Semi-generative Module
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Figure 10: System Structure of t h e Proposed G T Based C A P P System
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Figure 11: Architectural Overview
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Figure 12: Process Planning External Architecture
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Figure 13: ICAPPS System
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Figure 14: Extracting Generated Surfaces
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Figure 15: Flow Chart of Process Planning
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Figure 16: Functional View of C M P P
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Figure 17: Major C M P P C o m p o n e n t s
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Figure 18: Data Base System
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Figure 19: Part Input System
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Figure 20: Process Planning System
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Figure 2 1 : Typical Steps in the Assembly of a P/CB
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Figure 22: A C I M Architecture for the Production of Electronic Systems
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Figure 23: T h e CAPP-Postprocessor Relationship
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Figure 24: Sample Product R o u t e List
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Figure 25: Master R o u t e Flow
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Figure 26: M R P View of the Master R o u t e
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Figure 27: W F C View of the Master R o u t e
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Figure 28: F D C View of the R o u t e Master Flow
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Figure 29: Data Relationship Between the Process Master and the R o u t e View
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Figure 30: Physical Operations, Typical Manufacturing Facility
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Figure 3 1 : Traditional Building Control Focus
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Figure 32: Integrated Manufacturing Facility
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ν
Computer-Aided Process Planning (CAPP)
1. Introduction
1.1 System Organization
Given the engineering design of an item which has to be manufactured, process planning is the act of
generating an ordered sequence of the manufacturing operations necessary to produce that part within the
available manufacturing facility.
For maximum efficiency, the developed process plan should produce the part at the lowest cost consistent
with acceptable quality standards and using established procedures. In achieving these aims, it is essential
that process plans for parts which are basically similar should be standardized.
Traditionally, process planning has been regarded as a manual operation, usually carried o u t by a
manufacturing engineer (process planner, process engineer, etc.) who is often a qualified and experienced
machinist or tool maker. T h e success rate achieved by an individual planner is largely dependent upon
individual skill and aptitude for the planning task, knowledge of manufacturing processes, equipment,
materials and methods in general, and those available in a production facility in particular.
T h e rapid evolution of increasingly sophisticated production methods, the ever increasing trend towards
the use of flexible manufacturing systems, and the need for improved manufacturing efficiency has
necessitated a requirement for improved process planning. T h e use of computers to achieve this is now
well established, and new computerized methods are continually being sought.
1.1.1 Traditional Process P l a n n i n g
Traditional process planning methods usually allocate planning jobs to the next available planner. Each
task is therefore treated as a new process plan with usually limited attention being given to process plans
for similar parts already in existence. As a result, each process plan will reflect primarily the skills and
experience of the individual planner concerned; hence, it is extremely difficult to maintain consistency and
discipline in the planning process. Process planning also requires the use of many complex disciplines
including sequencing, machine selection, time and motion study, programming, and material flow to n a m e
some of the most common. All of these skills are needed in an increasingly complex manufacturing
environment and are making it even m o r e difficult to produce efficient process plans.
Several studies have been conducted to investigate the efficiency of manual process planning methods.
O n e , conducted by Cincinnati Milacron, reports the results of a study into the process planning for the
production of a family of spur gears. F o r a sample of 425 relatively simple spur gears, there were 377
different process plans (operation sequence and machine groups), 54 different types of machines required,
and 15 different materials utilized. T h e plans gave 252 unique combinations of machine tools for
successive operations. T h e inefficiency arising from this situation must be obvious to anybody with
manufacturing experience.
A perfect example of the problem concerns the production of the simple part shown in Figure 1, together
with the processes proposed by four different process planners. T h e four different methods of producing
the 18 m m hole are readily apparent and obviously reflect the past experience of the individual planners
concerned.
Attempts to standardize and rationalize the process planning task revolve around the maintenance of card
index systems which relate to previous plans. Such systems quickly become outdated or are, at best, very
cumbersome to use. T h e use of a computer for storing such data was an obvious first step and the first
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Computer-Aided Process Planning (CAPP)
CAPP systems were basically just computerized card index systems.
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2
3
4
5
6
7
8
9
10
Turn 30
Face Cut
Drill 1 5 °
Countersink
Turn 30
Drill 1 8 °
Drill 17.5°
Thread Cut
Turn 30
Drill 16°
Bore 18°
Thread Cut
Bore 18°
Thread Cut
Face Cut
Face Cut
CutOff
CutOff
Second Face Cut Second Face Cut CutOff
Second Face Cut
Face Cut
Turn 30
Countersink
Drill 16°
Bore 18°
Chamfer
CutOff
Second Face
CutChamfer
Thread Cut
Figure 1: Production of a Simple Part
1.1.2 Classification and Coding
T h e number of different part numbers which flowed through most manufacturing facilities were such that
they made the initial card index approach only a very marginal improvement on the manual systems which
they superseded. T h e development of standardized process plans required the identification of part
families where such families can be distinguished by the sequence of manufacturing operations required.
Several part families may share common machine tool routings but a unique production part family has
the same, or nearly t h e same, list of operations. T o define part families, it is necessary to have some form
of parts classification and coding system.
Classification and coding systems are often considered to be a part of the G r o u p Technology (GT)
production concept. However, classification and coding systems have advantages quite separate and
distinct from their use with G T . F o r example, a well designed classification and coding system can provide
significant advantages in the basic engineering design process by reducing the number of drawings and
different part numbers which commonly occur over a period of time through the duplication of part
designs which perform the same or similar function.
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Computer-Aided Process Planning (CAPP)
When used with G T , the benefits of classification and coding can be summarized thusly:
•
T h e formation of part families and machine groups
•
Quick retrieval of designs, drawings and production plans
•
Design rationalization and reduction of design costs
•
Secure reliable workpiece statistics
•
Accurate estimation of machine tool requirements, rationalized machine loading, and
optimized capital expenditure
•
Rationalization of tooling setups and the reduction of set-up times and overall production
times
•
Rationalization and improvement of tool design and the reduction of tool design time and
cost as well as tool fabrication time and cost
•
Rationalization of production planning procedures and scheduling
•
Accurate cost accounting and cost estimating
•
Better utilization of machine tools, work holding devices, and manpower
•
Improvement of Numerical Control (N/C) programming and the m o r e effective use of N/C
machines.
Many of these benefits can be achieved without using them in conjunction with the G T cell concept.
T h e r e are a large number of proprietary classification and coding systems available ranging from the "look
and see" approach to large numerically coded systems. T h e most well known systems include among
others, the O P I T Z system developed in Germany, the MICLASS system developed in Holland, and the
B R I S C H B I R N system developed in Sweden. In practice, most proprietary systems have been found to be
inadequate for particular company applications and most successful classification and coding systems have
been developed by adapting a basic proprietary system to suit the needs of the particular facility concerned.
A basic problem in using any classification and coding system is the h u m a n problem of applying it to
particular parts; i.e., different people using the same coding system will arrive at different codes for the
same part. Most applications nowadays therefore, use computer assistance in order to obtain standardized
coding. O n e such aid is the D C L A S S system developed at Brigham Y o u n g University, which can be
utilized in conjunction with any classification and coding system to obtain consistent results. This system
is an interactive system which enables a planner seated at a C R T to obtain a classification code by
responding to a series of system produced queries.
T h e basic starting point of a C A P P system is the implementation of a good classification and coding
system. However, work put into classification and coding has many other useful applications in the
manufacturing and design environments, such that implementation costs can b e easily recouped from
efficiency improvements.
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Computer-Aided Process Planning (CAPP)
1.1.3 CAM-I CAPP
O n e of the earliest C A P P systems was developed under contract to C o m p u t e r Aided ManufacturingInternational, Inc. (CAM-I) in the USA. CAM-I is a not-for-profit organization, formed in the U.S. in the
early 1970s by a number of major American manufacturing companies, to provide leadership in the
development of computer aids to manufacturing industry. CAM-I is now an internationally recognized
body with member companies in the U.S., E u r o p e , and the Pacific Rim. T h e C A P P program has since
been used and adapted by CAM-I m e m b e r companies for their own use and thus forms the basis for many
of the well-known company sponsored systems. Two versions of C A P P are now available for 16 bit and 32
bit computers, respectively. Both versions are identical in operation and effect.
C A P P is based on the use of a classification and coding system to group parts into part families. Each
part family has a common, or nearly common, process plan, which is stored in the computer as a standard
plan for that part family. Each standard plan is a sequential set of instructions that includes general
processing requirements, jig and tool data, machine data, and detailed operating instructions. In the CAPP
system, these standard plan details are called work elements and work element parameters. T h e system
allows for these items to be referred to in any format which will suit the normal facility terminology. In
addition, the C A P P system permits the use of any classification and coding system up to a maximum of 36
digits.
C A P P is an interactive system which permits a planner to sit at a terminal and locate process plans, modify
existing plans, or carry out any other normal process planning operations without any need to know
computer programming. C A P P is written in standard ANSI F O R T R A N - 7 7 ; however, two or three of the
sub-routines involved are machine or terminal dependent and may require modification to suit particular
installations. In general, however, the use of F O R T R A N - 7 7 does mean that user modifications can easily
be built into the basic C A P P program. CAM-I only aims to produce prototype software and a particular
implementation of C A P P requires some debugging effort on the part of the user.
1.1.4 The CAPP System
Basically C A P P requires a data structure of six main files: part family matrix file, standard sequence file,
operation code table, operation plan file, part family code table, operation plan file, part family set-up file
and a process plan store file. T h e flow diagram in Figure 2 gives an overview of the sequence of
operations.
System operation is menu-driven. T h e particular operation to be carried out can be called by invoking the
particular m e n u concerned and responding with coded commands to carry out the operation required.
Process plan data, process plan header data, part numbering, and other data are all inserted using normal
facility nomenclature and formats. Although this data is specified during system setup, it can easily be
altered later as facility requirements dictate. T h e part family matrix file contains the part family codes in
the form of a matrix as shown in Figure 3.
T h e C A P P system allows for a 35 digit coding format with up to 16 permissible characters for each digit.
T h e system also allows for part attributes to use up to four digits for coding and for multiple characters to
b e used in each digit. T h e part family matrix file, therefore, allows great flexibility for the user to select a
classification and coding system which gives him the greatest possible benefits.
T h e C A P P system requires the user to develop and store a standard process plan for each family. Each
process plan contains header data which can be initialized by the user for the types of information needed
on the printed process plan and for any language desired. Approximately 100 items are available as shown
in Figure 4. A user specified header menu is built up when the system is initialized and appropriate data
is inserted into the menu when a new process plan is generated.
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Computer-Aided Process P l a n n i n g (CAPP)
Standard
Sequence
File
Part
Family
Matrix
Part
Family
Search
Header
Input
Data
Standard
Sequence
Retrieve/Edit
Part
*\
Classification
V
Code
J
Process
Plan
Process
Plan
Formatter
(
Application
Programs
Operation
Ran
File
Work
Element
Processor
Operation
Plan
Retrieve/Edit
Process
Plan
Store
F i g u r e 2: O p e r a t i o n s Overview
Code
Char. Γ
1
Set
Classification Code Length
I
2
3
4
5
7
6
0
1
8
9
11
10
X
2
X
X
3
X
4
X
X
X
X
X
X
X
X
X
X
X
X
X
X
7
X
X
8
X
9
X
X
A
X
X
Β
X
1
2
,
3
1 4
5 .
6
„7
I
8
16
X
X
X
15
X
X
6
5
14
13
X
X
X
12
X
X
X
1
I
9
I
10
,
11
,
I
Part Attributes
Figure 3: Part Family Matrix File
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Computer-Aided Process Planning (CAPP)
Header Data Elements
Identification
Reference
Part No.
Part Name
Part Family No.
Plan Type
Issue No.
Etc.
Part Type
Source
Standard Cost
Lead Times
Project
Etc.
Usage
Material
ι
I
Next Assy.
Effectivity
Quantity
Units/Prod.
Etc.
Material Code
Material Size
Material Spec
Weight
Supplier
Etc.
I
1
Planning Change
Miscellaneous
Change Letter
Change Planner
Change Date
Etc.
Work Standards
Standard Times
Q.A. Class
Order No.
Mfg. Source
Figure 4: Process Plan
Each process plan is built by invoking a set of operation codes (op codes), each of which identifies a
unique operation. T h e o p codes are set up during initialization in the op code file and operation
descriptions can be in the standard facility format. Each process is numbered and cross referenced to the
part family number to which it refers. The standard plan structure is shown in Figure 5.
Operation Plan
(OP Plan/OP Codes)
• M / C Number
Dept
Work Center IM/C Reference
1 Location
M/C Code
Set Up Data
Time Stds Data
Work Elements or
Work Instructions
Work Element
Parameters
Figure 5: Standard Plan Structure
6
Computer-Aided Process Planning (CAPP)
T h e basic C A P P system requires the user to insert his own time standards, but several companies have
found it a fairly straight forward operation to link a computerized standard time program to the system.
T h e C A P P system also allows for unique part process plans to be stored separately for parts which do not
reasonably fit into any commonly used part family.
T h e operation of the system requires the user to feed in the classification code for the part concerned.
T h e system searches the part family matrix file and attempts to fit the part into a part family for all the
digits in t h e code. If unsuccessful in matching all digits, the system will find the part family which matches
the earlier digits in the code and will tell the user how many digits can be matched. Once a part family
has been found, the process plan for that family can be called up on the screen. T h e process plan can be
used as is or can b e modified where necessary for a particular part, and header data can b e altered. If a
standard plan is used as is, the part number concerned is added to the list of the part numbers which form
a part family. If a standard plan has to b e modified, it can be stored as a separate part plan, printed out
and then deleted, or stored as a revised process plan for the appropriate part family. T h e basic system
menu and o n e of the sub-program menus are shown in Figure 6, as examples of the system in operation.
CAPP is comparatively simple to use, once it is set up, and requires no special computer skills from the
process planner. T h e system has been operated successfully by many companies in its basic form.
However, it was first used in 1976 and some of the major companies who started with the system have
made modifications to enhance its usefulness and to make it m o r e compatible with their own operations.
1.1.5 CAPP Developments
CAM-I C A P P is known as a variant process planning system; i.e., it operates by taking an existing process
plan and changing it to suit the new part. T h e r e are, however, obvious advantages in being able to create
a brand-new process plan for each part as required. Systems which o p e r a t e in this way are known as
generative process planning systems and development work on such systems has been the subject of much
research over the last decade or so.
A generative process planning system must be capable of applying a set of rules and massive amounts of
data to the construction of a process plan in much the same way as a human planner reasons when he
constructs such a plan. Hence, the development of a generative process planning computer system
requires the use of computer systems termed artificial intelligence (AI) systems. M o r e specifically, current
research is based a r o u n d a subset of AI technology called knowledge-based expert systems. Expert systems
consist of a factual database and a set of inferential or heuristic (rule of thumb) rules which use the factual
database to solve problems.
Investigations into heuristic methods of process planning define process as a problem which is only defined
by its target (finished part), starting point (raw material), and a set of constraints (available processes and
equipment and technological relationships). In addition, it is probably necessary to introduce time/cost
criteria to choose an optimal solution. T h e conclusions from such studies tend to agree that the use of
expert systems or AI are probably the most promising way to tackle the complex relationships involved in
the planning process.
1.1.6 CAPP a n d CAD/CAM
C A D / C A M systems have been developed to the point where a design engineer and a manufacturing
engineer seated at graphics terminals connected to a common computer database can produce parts from
computer designs without benefit of paperwork at any point. Thus, engineering drawings, process planning
documents, and other manufacturing paperwork are all stored in the computer. If the computer is
connected directly to the appropriate C o m p u t e r Numerical Control (CNC) machines as in a flexible
7
Computer-Aided Process Planning (CAPP)
CAPP SYSTEM MAIN MENU
FS
FP
DP
HD
OS
Part Family Search
Format Plan
Delete Plan
Create New Plan
Retrieve Header
Retrieve OP Code Sequence
Retrieve OP Plan
Process Plan Review
Logoff
OP
PP
LO
FS
FP
DP
HD
HD/ (Part No, Plan Type, Status)
OS/ (Part No, Plan Type, Status)
OP/ (Part No, Plan Type, Status)
PP/ (Part No, Plan Type, Status)
LO
Space for inserting code for menu item required, e.g. FS
Part Family Search
MS
SP
DS
Matrix Search
Retrieve Standard Plan
Display Plan No's
Search Attribute
Continue Search
Return to Main Menu MM
Logoff
SA
NS/
SP/
DS/
SA/
CS
MM
LO
CS
MM
LO
(Classification Code)
(Part Family No.)
(Part Family No.)
(Attribute No., Value)
Space for inserting code for menu item required, e.g. DS/26
Figure 6: Basic System Menu and Sub-program Menu
manufacturing system, the process plan can be followed without the need for human intervention. Current
C A P P systems make this possible, the newer C A P P systems will obviously enable it to be done even more
efficiently.
L 2 C A P P a n d GT
Current industrial applications indicate that the combining approach of variant and generative CAPP
methods is suitable for practical usage. A variant model is found most applicable for those products which
the company produces regularly, and a generative model is useful for the parts for which engineering
designs and manufacturing requirements vary. Since the current state of the art of the generative method
requires further development, it is m o r e practical to develop a semi-generative method which combines the
specific features of variant and generative approaches.
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Computer-Aided Process Planning (CAPP)
1.2.1 Group Technology
As noted above, G T is a manufacturing philosophy which identifies and exploits the underlying sameness
of parts and manufacturing processes. In conventional piece-part manufacturing, each part is treated
uniquely from design to manufacture. However, by grouping similar parts into part families based on
design or process information, it is possible to reduce manufacturing costs.
G T classification and coding and part family concepts have been used as the key elements for most variant
C A P P systems, which obtain the process plan by retrieving and modifying the part family-related standard
process plan. T h e application of G T classification and coding and part family concepts are used, not only
for classifying the parts, but also as the foundation for constructing logic and rules for generating process
plans. T h e system provides a highly automated C A P P process which generates the applicable process
plans. T h e system is relatively easier to develop and program, and needs less computation time and
storage space than most of currently available generative C A P P systems.
The implementation of an in-house G T oriented C A P P system is a multi-phased procedure and must be
introduced in steps. T h e proposed method makes the maximum usages of the G T concept. T h e entire
process includes developing an in-house G T classification and coding system, forming part families,
building an effective manufacturing information retrieval system, and developing the in-house semigenerative C A P P system.
1.2.2 GT Classification
The first and the most important step for implementation of G T is developing a suitable classification and
coding system. Many generic classification and coding systems and schemes have been developed in
various forms. They are readily available but not directly applicable in their original form, without being
properly modified and tailor-fitted to meet the specific needs of a particular application.
A tailor-fitted process contains three steps. First, a random sample of parts for a fixed production period
is collected. T h e sample is used as representative of the whole population of parts that is produced.
Second, a suitable publicly available system is used for sample coding of selected sample parts. Third, the
statistical data of the sample part population is evaluated using the coding results. T h e trial system is
modified, based on the sample coded results and also to meet the specific needs of the application.
Following these exercises, an in-house classification and coding system with 13 digits is developed. T h e
system contains such information as part type, general shape, material, operation and surface finishing
requirements, and heat-treatment. Figure 7 shows the outline of the classification and coding system. A n
effective, user-friendly, menu-driven computer program can be developed on a personal computer.
1.2.3 P a r t Families
Since most of the benefits obtained from applying G T are based on the underlying sameness of parts and
their manufacturing processes, the method used to form the proper part family is a very critical element.
T h e methods of forming G T part families have been improved using appropriate mathematical
programming techniques and suitable computer programs. T h e simple ocular observation method and the
manual production flow analysis method have been replaced by computerized methods using suitable
algorithms. Recently, many advanced methods including cluster analysis and pattern recognition
techniques have been proposed to form the G T part-families.
Most of the existing cluster analysis algorithms for forming G T part families use production flow data as
the input. T h e part families formed by these methods are operation-sequence dependent and do not
reflect the design aspect. However, from the computer integrated manufacturing implementation point of
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Computer-Aided Process Planning (CAPP)
DIGITS
DESCRIPTIONS
1 & 2
Product Type
3 & 4
Material
5
Size Parameter 1
6
Size Parameter 2
7
Size Parameter 3
8
Shipping Weight
9
General Shape
10
Operation and Accuracy (Outside)
11
Operation and Accuracy (Inside)
12
Operation and Accuracy (Ends)
13
Heat Treatment
Figure 7: Outline of an In-house Classification and Coding System
view for standardization of design, process planning, and other implementations of the G T concepts, part
families should reflect both design and manufacturing characteristics. Since a well-designed G T
classification and coding system should reflect correctly both manufacturing and design characteristics, part
families reflecting both design and production processes can be obtained. The actual industrial
applications using G T codes and multi-objective cluster analysis provides a method that can form the G T
part families and retrieve similar parts and related part families properly.
1.2.4 Information Retrieval System
A n important task in large manufacturing concerns is identifying and analyzing the numbers, types, and
characteristics of parts being produced. All manufacturing, planning, and control functions are dependent
on the understanding of the part population and its manufacturing requirements. With an interactive
computer program, this information retrieval system easily finds the required production features, the
material types, and operation requirements based on the specific priorities required.
It is always the desire of management that, at any given time, the part population of the factory is precisely
known in terms of part specifications, production requirements, and part features, so that an information
base exists for use in design rationalization, manufacturing planning, production control, marketing, and
purchasing decisions. U n d e r a G T environment, this includes the ability to retrieve and group part
families for use in various manufacturing functions. Without a well-designed classification and coding
system, retrieval of required manufacturing information is difficult.
10
Computer-Aided Process P l a n n i n g (CAPP)
1.2.5 Variant CAPP Module
T h e first step in building a relatively proficient C A P P system is to use the variant approach. As in most
variant C A P P systems, a standard process plan can be automatically retrieved for a new order, using its G T
classification code and the part family number. T h e built-in standard process plans are entered for each
part family, and the final process plan for a particular part can b e obtained by editing the standard process
plan.
T h e unique feature of this particular variant C A P P module is that it uses a multi-objective clustering
algorithm as t h e part family searching mechanism instead of using the part family matrix matching or G T
classification codes matching method like most GT-based variant C A P P systems. T h e advantage of using
this method is that if the new part cannot be grouped into an existing part family, a number of similar
parts and their part families can be reached according to different searching requirements. In this way, the
user can develop the new standard process plan based on some other similar parts and their part family
related standard process plan.
The structure of the variant module is shown in Figure 8. In order to obtain the process plan for a new
part, the part must first be coded. Using the interactive coding program, a G T code can be assigned to the
new part. After the part is coded, the user needs to input the priority for the part family searching. For
instance, if a new part has the particular requirement on operations, the user can put the digits of
operation requirements as higher priority digits. If, however, a part is made of special material and needs
special heat treatment, then the user can specify the digits which describe the material and heat treatment
as m o r e important features. A similar part and part family can be retrieved and the standard process plans
of these retrieved part families can be obtained from the standard process plan data file. T h e final process
plan for the new part is obtained by modifying the retrieved standard process plan. A practical industrial
application shows that the multi-objective clustering algorithm-based variant C A P P system can classify a
part into a part family or find the proper part families m o r e accurately for the new part than other
variant-type C A P P systems. Using the relational database management technique, the computation time
for searching similar parts and part families can be reduced tremendously.
1.2.6 Semi-Generative CAPP System
Using the variant process plan, the final process plan for a particular part can be obtained by editing the
standard plan. Nevertheless, it requires the process planner to make decisions at the editing stage. In
order to improve the performance of the C A P P system further, an application-oriented, rule-based semigenerative C A P P system can be developed to enhance the proposed variant system.
1.2.6.1 Variant and Generative C A P P Module
Although a variant process planning system can help the process planner to make the process plan
efficiently, the person using the variant C A P P system must be an experienced process planner, so as to be
competent in making decisions during editing the standard plans. Therefore, the variant process plan
system is usually suitable for preparing process plans for those parts which have relatively stable process
routes.
When there are many differences between the process plans of the similar parts, it
a generative process plan system. Instead of using existing standard process plans,
plan system utilizes built-in logic to select and sequence necessary operations. All
process planning procedure are m a d e by the system, and the o p e r a t o r need not be
planner.
11
is m o r e suitable to use
a generative process
of the decisions in the
an experienced process
Computer-Aided Process Planning (CAPP)
Coding
Part Family
Searching
Semi-Generative
Main Logic Tree
Editing
Process Plan
Figure 8: Structure of Variant Module
Developing a generative process planning system, however, is really an enormous task. A truly generative
CAPP system is hard to construct. E n o r m o u s activities are involved in developing such things as general
process planning logic sets and constructing a suitable database structure.
Since most so-called generative CAPP systems require that the user key-in part features, generated process
plans are therefore dependent on how the part features are interpreted. In addition, a completely
generative C A P P system makes every decision in the process planning procedure from scratch. This
requires tremendous computer memory and computation time.
1.2.6.2 Semi-generative CAPP Module
T h e activity of process planning is a company-oriented task. This means that even a manufacturing
process which has been successfully used in o n e company might not be suitable for producing the same
part in another company, because of different manufacturing conditions, machine tools, skill of the
workers, corporate culture, and unions. Therefore, it is hard to build a generic generative CAPP system
which can be adapted for different manufacturing systems. However, when applying specific manufacturing
applications, the task of developing the generative logic for process planning is greatly simplified.
Based on the above considerations, a semi-generative CAPP system holds promise for many applications.
T h e reason that the system is termed "semi-generative" is that both a variant retrieving method and a
generative decision logic approach are used. Some decisions are generated by the built-in, process
12
Computer-Aided Process Planning (CAPP)
planning generating logic, while some other process plan decisions are retrieved in the form of tables and
decision sets.
T h e G T part family concept is applied as the key element for constructing the rule-based C A P P expert
system. Instead of developing the process planning logic based on part features like most other generative
C A P P systems did, the process planning logic or decision rules are divided into two types; part family
related decisions and operation related decisions.
T h e part family related logic is the set of logic using the part family as the driven machine. Since different
parts require a different process plan which is generated by a different logic set, similar parts can share the
same process plan logic set. Therefore, the logic used for generating the process plan can be simplified by
using the part family concept. In the part family oriented logic set, the decisions are made step by step
according to the part family number. In each node of the logic tree, the operation or operations, division
number and machine number will be defined. T h e detail operation instructions can be further retrieved by
the operation number. Detailed operation instructions, like operation sequences, machine selections,
machining parameters, and time standards can be generated with very few computations.
T h e other type of decisions are operation related. They are the rule sets which are related to operations
rather than part families. F o r instance, some parts have auxiliary holes which should be drilled or drilled
and tapped. However, there exist various combinations on radial or axial holes, the location of the holes,
and the diameters of the holes. This is a set of decisions which is independent from the part families; e.g.,
a rule set called drilling. Depending on the size, location, and type of hole, parameters such as operation,
operation sequences, and machine station can be obtained.
The method of developing the generative process planning logic using G T part family concepts simplifies
the procedure of constructing the process planning logic. Because of this simple and clear logic tree, the
computation time is reduced.
1.2.6.3 System Structure
T h e system structure of the semi-generative C A P P module is shown in Figure 9. T h e part to be planned is
coded first, using the in-house classification and coding system.
After coding, the part will be automatically classified into o n e of the existing part families, if o n e is found.
T h e main process plan logic calls the part family oriented rule sets and operation oriented rule sets, the
machining and operation data bank, and time standard data bank and generates the process plan. Figure
10 shows the flow diagram of the entire system.
13
Computer-Aided Process Planning (CAPP)
Figure 9: Structure of the Semi-generative Module
14
Computer-Aided Process Planning (CAPP)
^
Start
MOCA PF
Searching
CED
Figure 10: System Structure of the Proposed G T Based CAPP System
15
Computer-Aided Process Planning (CAPP)
2. System Implementation
2.1 Developing t h e Process P l a n
T h e basic information which links quote/order processing data with process planning data includes the part
number, part description, and stock number. The part master identifies all of the resources which the
company builds or uses in serving its customers. With data from quote/order processing, delivery
requirements are established by date and quantity. With this information in place, automating the process
planning function can proceed.
2.1.1 Basic Considerations
T h e first step in automating the process planning function is selecting a few jobs and defining procedures
for developing formal process plans and defined a series of operations. A less formal plan consists of
simply a "build to print" instruction. Most major manufacturers require a format which spells out all of
the manufacturing requirements, including material, operations, tools, fixtures, gauges, and inspection data.
It also provides details about setup and fixturing, speeds and feeds, workpiece orientation, dimensions and
tolerances, and step-by-step process descriptions, including Q C .
Process engineers develop these plans on sheets summarizing the manufacturing process, which usually
accompanies the workpiece as it travels through the shop. These summary sheets are called travelers or
routers and are a necessary part of process planning.
2.1.2 D a t a b a s e Contents
Every workpiece, tool and fixture must have a manufacturing plan or set of plans. These plans must be
stored in an easily accessible manner. T h e r e can be more than o n e plan for manufacturing a particular
item, because different machines may be used or a special rework plan may be needed.
Each computer record should identify tools, fixtures, N/C programs, machines, setup times, piece times
(labor and machine), and detailed operation instructions. Vendor operations and inspections must also be
identified.
Materials, tools, fixtures, and other elements required for an operation should b e specified and tracked to
b e sure that they are in inventory, scheduled to b e made, or ordered in time to meet production
requirements.
Routers, travelers, and other work control documents must accompany single workpieces or sets of
workpieces in production. T h e paperwork must list the operations in summary form in a manner
consistent with the plan. Workpieces for a particular job must be grouped in lots. Lot size can vary from
o n e to the total order quantity.
Information defined in the process planning module serves as a basis for estimates and quotes. Labor
vouchers are validated against the plan. Based on what the labor voucher shows, the production control
department can estimate how the j o b is progressing and where trouble spots or bottlenecks might be. T h e
plan helps production schedulers estimate the load on each workstation and foresee contention.
Standard times help job costing by establishing a baseline against which actual costs can be measured.
Work performance can be measured on an equivalent unit basis, a frequent requirement for large contracts
with progress payments.
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Computer-Aided Process Planning (CAPP)
2.1.3 Start-Up Methods
T h e r e are several ways to begin orienting process planning toward computer augmentation:
•
Produce a highly detailed process plan for every workpiece. These plans are prepared
manually, then copied and updated as needed. To start, select several jobs and use a process
planning method to prepare the paperwork for the master plan and the travelers. This
approach has little impact on production and allows the shop to experiment with the software.
It also facilitates training.
•
Use the existing process planning system. Develop data conversion programs to move the
data from the existing system to the new system. Data is moved all at once and everyone uses
the new system immediately. Although this immediate conversion can put pressure on users,
they have the advantage of moving from o n e automated system to another. This prior
experience eases the transition from the manual system to the automated one.
•
Develop a prototype process planning module, designed to gradually introduce the idea of
automated process planning to the engineering department and to establish a standard method
of defining plans and releasing work to the shop floor. This prototype is simpler than the
finished system, but all of the basic information can be captured and transferred to the new
system. A n internal data processing department provides resources to support this kind of
independent effort.
•
Introduce automated process planning to the shop gradually. Keep a skeleton plan on the
system, but develop detailed process sheets with word processing software on PCs. Thus, the
most labor intensive aspects are handled off the system. Copies of the master plan, with all of
the operation sheets, are kept in a master file and backup copies of the P C files are kept for
security.
2.1.4 Educating t h e User
Process plans are the heart of any good system, but creating good plans is very difficult. Sharing
information is the major challenge. For example, engineering departments do not always have the best
information. Engineers must stay in touch with production control and shop floor foremen. Separate
departments have a tendency to isolate themselves and to make decisions based on incomplete
information. Access to a central database helps solve this problem.
Process planning requires identifying the best technical as well as the most economically feasible means of
producing a part. Sequencing operations, selecting the right machine, and estimating the duration of each
operation are among the most difficult pieces of information to collect or define. Rush or non-standard
jobs are particularly difficult to handle.
Establishing standard times for operations sparks the greatest controversy. Engineers feel that, without
actual timings or shop floor data, they are guessing. Operators feel threatened by the standards, which can
create the impression of poor performance if set unrealistically high. Managers worry that some
employees will slack off if standards are too low.
Most of these problems can be solved by education. As planning is implemented and work release
controlled, shops begin to collect shop floor data against the plans. T h e original estimates are replaced
with standards based on actual data collected. This relieves the burden on the engineering staff for
collecting and analyzing data. Publishing standard times and explaining their use eases the concerns of
operators as well as managers. Operators are able to evaluate goals and judge whether or not they are
18
Computer-Aided Process Planning (CAPP)
realistic. In some cases, managers are surprised to find that operators are eager to recommend
improvements and identify problems once they understand what is expected of them.
Shops must accept the basic premise that the definition of the plan becomes the standard against which
performance is measured. Therefore, it is extremely important to create plans carefully and follow them
closely.
A major area of difficulty is the process of work release and determining manageable lot sizes.
Introducing formal work release procedures requires each production run to have its own original traveler.
Those in charge of work release have to learn to assign jobs to specific plans and create individual
travelers for each lot of workpieces. Several problems typically occur:
•
Some production control personnel create single lots for the entire order quantity, even when
a large number of parts are to be delivered over a long period of time. These lots are
obviously too large and impossible to schedule or track effectively.
•
Some individuals create lots based on container size; e.g., if a tub holds eight pieces, a lot of
eight pieces is created.
•
Lots are created using the wrong process plans. Often, multiple plans for the same part exist,
depending on what has to be done to the part. This situation creates the danger that the
wrong traveler might be used and released to the shop floor.
Education provides the solution to these problems; e.g., a lot is defined as a quantity of parts in
production that can b e tracked and scheduled in some near term capacity. T h e concept involves
determining lot sizes based on delivery requirements. O n e or m o r e sets for shipping can be combined to
make a single lot. Likewise, production control personnel can determine lot sizes based on the most
economical quantity to produce according to delivery dates.
Customer orders with "as required" delivery dates can be a problem. Scheduling these orders is difficult
because the quantities and delivery dates are not known. These orders are handled "on demand" and
worked into the schedule as time permits.
2.1.5 Procedures
Establishing standard procedures and creating automated tools to support them is a lot of hard work but
ultimately streamlines the process. In addition, keeping plans in a central place helps to meet the demand
for documentation, planning, and traceability. Online displays allow users to view plans and travelers as
they are being created.
T h e bill of materials lists resources for every operation. These resources can be other workpieces, various
materials, tools, fixtures, or anything that is required to perform the operation. If the resource has to be
made, a plan is developed and a resource-traveler created. In this way, a tree of plans can be constructed
to correspond to the production requirements of a particular assembly.
Split lots are always a problem. T h e most c o m m o n reason for splitting is to meet schedule demands of
customers. T h e procedure to solve this problem provides traceability of lots as they split. When a lot is
split, the last successful operation of the original lot is identified. Then o n e or m o r e parts can be
separated to form a second lot for additional processing. This method provides a history of the job
through production.
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Computer-Aided Process Planning (CAPP)
2.2 Selecting a n d Implementing a C A P P System
2.2.1 Approaches
Two of the most difficult questions confronting the selection of a C A P P system are:
•
What system best suits my company's needs
•
W h a t steps are required to successfully install the system or systems chosen
T h e probability of o n e system's fulfilling all of a company's needs is relatively small. As o n e might expect,
n o single system performs every function required by a company. F o r example, some systems interface to
design, through the ability to translate I G E S (Initial Graphics Exchange Specification) files. These systems
are able to communicate with C A D systems more readily than systems without this capability. However,
companies manufacturing products to customer's designs have little control of design. They may not be as
interested in the ability to perform design retrieval for productibility analysis and standardization. O n the
other hand, those same companies might be very concerned with the ability to transmit C A D data, CAPP
instructions, and machine language instructions to the customer's plant or to distribute customer
information throughout their factory or among plants in geographically diverse locations.
Moreover, the product manufactured might lend itself to either variant or generative CAPP systems. In
generative environments, companies may wish to consider a rule base for design producibility as well as a
rule base for manufacturing instructions. In variant environments the ability to direct process planners or
design engineers to preferred practices is desirable. If left uncontrolled, variant systems may direct users
to a number of similar designs or processes, but unless steps are taken to prevent it, the user may select a
poor design or process on which to base the variant.
T h e mix of products manufactured may be an issue. In metal working environments in which G T and
process planning originated, traditional G T codes perform satisfactorily. However, in companies producing
printed circuit boards (P/CBs) or complex electromechanical devices, classification by shape may be
unimportant, or perhaps useless, while the classification of other features, such as the components
contained on a P/CB, will require the classification power of a relational database to perform effectively.
Further, in these instances, ANSI S Q L or other relational database application languages are often
required to make use of the data classified. For example, it is not always the case that a design or
manufacturing rule may be based solely on the presence or absence of data in a single classification field.
In most instances, manufacturing rules are contingent on a variety of characteristics. So, for example,
when planning the manufacture of a P/CB, o n e might wish to know whether the components mounted on
the board may be inserted automatically by machines. A component that is normally machine insertable,
however, may not be machine insertable, if it is located in close proximity to a larger component that
interferes with the insertion head. Because many large components are not adaptable for insertion by
machines, they must be inserted by hand. In this case, the application language rules would call for the
insertion, if the larger c o m p o n e n t were absent o r located at a distance sufficient to safely insert the other
component. In the absence of these conditions, the process instructions would direct the individual along
a different course.
Work measurement is an issue at s o m e companies because of union agreements, compliance with military
specifications, or incentive payment systems based on piecework or other forms of measured output. In
these environments, the ability to standardize production methods and easily revise labor standards is
essential. T h e situations exist in competitive markets typified by repetitive production, such as that found
in consumer products.
In other environments, one-of-a-kind or custom designs produced infrequently make labor standards a
20
Computer-Aided Process Planning (CAPP)
relatively low-priority item required only for project control. In these very different environments, the
automated capability to measure human or machine-paced work will be weighted differently.
A n o t h e r factor compounding the selection decision is the difficulty involved with assessing the strengths
and weaknesses of competing systems whenever they approach the problem from different directions.
Many potential C A P P users, for instance, have situations in which both variant, generative, or
semigenerative approaches are appropriate. In these instances, evaluating a purely generative system
against a purely variant system can be quite difficult. Likewise, the differences between systems'
capabilities to interface with other business systems, such as Manufacturing Resource Planning ( M R P ) ,
also vary considerably, further complicating attempts to make a solid evaluation.
A n alternative approach, then, is to identify the business needs to be addressed by the systems under
consideration and assess the degree to which competing systems meet business needs. This approach
avoids fruitless attempts at comparisons between systems that approach the problem differently and also
identifies areas in which perhaps more than o n e system will be required in order to meet all important
business needs.
2.2.2 Identifying Business Needs
An approach to identifying business needs utilized by major consulting, systems, or engineering firms
involves flow charting the business systems to which the CAPP system must interface. T h e procedure
involves a system "walk-through" from point of origin to completion, while, at each stop, interviewing the
system users, collecting the documents and other information requirements used by the system, and finally,
flow-charting the information processing and distribution of documents and information throughout the
system.
2.2.2.1 System Walkthrough
O n e manufacturing engineering manager trained in systems design was amazed at the system interface
required to replace paper, pencil, and file cabinet process planning systems with a computerized one.
Even though his objectives were limited to automating the manual work, the information interface to
other business systems proved much larger than o n e might anticipate for so modest a goal. As pointed out
earlier, this is because the process plan contains information that permeates the business operation.
Accountants use it to value inventory and as the basis for standard costs. Standard costs, in turn, affect
pricing in the market. T h e difference between the market price and standard cost establishes profit from
the sales. Usually, estimating or quoting activities for new orders and delivery lead times are based on
manufacturing methods.
As these systems are automated, the cooperation with data-processing elements of the business must grow.
Communication of the information contained on the process plan must switch from paper to electronic
media. Now, communication protocols and the timing of information transmissions become important.
Because other data-processing users may now access the system, activities that previously lacked a time
dimension may now be constrained by one. For example, electronic process plans may all be required to
be u p to date and complete during the evaluation of a year-end inventory, or routing files may be absent
or out of date when an M R P run is under way. In paper and pencil systems, the most recent copy on file
always served this purpose. In electronic systems where only o n e image exists, it cannot be "locked out for
update" when required by other elements of the business system.
Many departments within the company rely on data contained in the process plan. Production scheduling
and control systems rely heavily on information within the process plan for lead time calculations and
capacity requirements for personnel and productive equipment. Make-buy decisions affect the purchasing
department, engineering bills of material, and process instructions. O n the manufacturing floor, routings
21
Computer-Aided Process Planning (CAPP)
may be used to report direct labor and material applied, trigger vendor operations, procure outside
services, and record quality transactions such as scrap, rework, or acceptance into finished inventory. In
some companies the process plan is used to report personnel-related information such as attendance or
tardiness. In incentive or piecework environments, it plays a direct role in the calculation of employee
earnings.
T h e raw materials from which products are made, the perishable tooling of materials used in its
production, and the capital equipment upon which it is produced constitute the largest source of
investment for most manufacturing companies. When this information is compiled and distilled by
management, strategic decisions affecting the company's course and position in the market are made.
T h e accuracy of the process planning database is crucial for sound business decisions, and the interface to
other business systems is important even when CAPP's immediate goal is limited to automating the
functions of paper, pencil, and file cabinet.
2.2.2.2 User Interviews
The most important step at each stage of the process consists of interviewing the users of the system.
These interviews are a source of invaluable information on the many small ways that improvements to the
system can be made. O n e should not be surprised to find that much of the data collected can be
eliminated because it is no longer utilized by any downstream process, many things currently being done
manually might be better d o n e electronically, and the throughput time required to sequentially process
through a paper system compared to that required for processing with an electronic system can be
dramatically reduced.
A n objective of the system designer should be to provide each user of the system with only the information
required. N o information should be collected that is not utilized elsewhere in the processing system.
Likewise, no useful piece of information should be omitted from the formal system design and
accomplished through informal methods. At this state of the system design, interviews with users are
important to gather information and understand how the system works so that the CAPP system can be
successfully interfaced. Later, when the design of the new system nears completion, the system installer
will once again return to these users to review the proposed design and verify that the planned system
meets their needs.
2.2.2.3 System Flow Chart
It is good practice to start at the origin of the information system. For most process planning systems this
will be at the point of quotation or order entry. From that point, o n e should follow the processing steps
through to the final system transaction and output.
At each stop, it is important to record the information input to the process step, the method by which the
information is processed, and the o u t p u t of that process. Flowcharts may be used to document the
channels through which the processed o u t p u t is forwarded. This is accomplished by interviewing the users
at each step in the process and collecting completed forms used to capture, process, or transmit
information. W h e r e electronic systems are involved, the same steps take place; however, the information
is captured in the form of software documentation for the electronic systems employed. Often, however,
electronic systems are not documented or are incompletely documented. In these instances, flowcharts
which identify each piece of information and the way in which it is dispositioned must be constructed by
the systems analyst.
This step, while time consuming, is very important. When the new C A P P system is installed, users of
22
Computer-Aided Process Planning (CAPP)
every business system to which it interfaces must receive the information required to perform their job or
function. These flowcharts, forms, and software documentation assure that their information needs are
met by the new C A P P system.
O n e of the ways in which this assurance is provided comes from the forms collected. As the
manufacturing engineering manager, mentioned earlier, progressed through sales order entry and the
various downstream departments, he noticed that many of the forms in use n o longer fit the information
processing system. In some cases, personnel simply used old forms because a supply of several hundred
still existed. These older forms often lacked a formal method for capturing important information and,
conversely, often provided blocks for information that was no longer useful.
T h e reason for taking examples of completed forms at each step in the business system is to identify
instances in which useless information is captured and not subsequently processed. Conversely, whenever
annotations are made on the reverse of forms, the margins of forms, or through informal channels not
provided in the formal business system, o n e can take steps to ensure that these deficiencies are corrected
and formally addressed in the revised system.
New business forms are very cheap when compared to the risk of processing incomplete information,
missing a customer delivery, or incorrectly pricing a major job. D o not succumb to the temptation to use
old, inappropriate forms simply because several hundred or several thousand exist in the office supply's
storeroom. Throw them out and design forms appropriate to the business needs of the system. Take
advantage of opportunities to install better controls through the use of serially prenumbered forms with
controlled distributions, whenever the importance of the activity being controlled, such as purchase orders
or manufacturing orders, so warrants.
After the information is collected, it must be distilled and digested so that the business system is
understood. This is accomplished through the use of flowcharts. Flowcharts record the activity that takes
place at each step, documenting the information input to the activity, the processing that takes place, and
the information content of the o u t p u t distributed from the activity. Flowcharts explain both the
processing of paper and the electronic-based business systems. As our manufacturing engineering manager
proceeded through the various departments, he documented the information that was received by each user
of the system, what he or she did with that information, collected examples of the completed forms used in
processing the information, and noted where the information was sent.
2.2.2.4 System Design
With the systems "walkthrough" completed, the system installer is in a position to construct a preliminary
system design based on the information requirements that must be met by the C A P P system.
Understanding of the information requirements that the C A P P system must provide to other business
systems and the timing and controls necessary for each process step at which that information must be
exchanged is a necessary function of this process. This understanding helps the installer to specify the
minimum capabilities of the C A P P system as well as other timing and execution issues that must be
addressed prior to installation of the system.
To complete the preliminary system design, the system installer will require the assistance and
participation of a number of other professionals. For example, expertise in the data processing,
accounting, and materials area is often required in order to assure that the redesigned system performs
adequately. With input from these personnel, a detailed system specification can be written and
implementation activities coordinated among several departments. T h e preparation of this specification
may be expected to touch most, if not all, of the company's business systems.
In addition to capturing and providing a processing system and destination for all the information, system
23
Computer-Aided Process Planning (CAPP)
design tradeoffs must also be evaluated. System architecture is often an area in which many alternatives
are available. In single-product systems, access may be controlled by the system manager through the
assignment of various file, field, o r device privileges appropriate to a variety of users. In multi-product
operations, however, coordination is much m o r e difficult. Decisions must be made to determine what data
is to be shared among various products, what is to be product specific, and how all the data within the
system is to be secured, maintained, and recovered if lost.
T h e transition from paper to paperless systems operation adds another dimension to the system design
effort. Sensitive or classified data must be protected. Since such data is most vulnerable during
transmission, o n e may expect to be required to secure the entire area in which transmission takes place in
order to satisfy the requirements of government security officers. Transmission on unsecured media is not
likely to be permitted regardless of password security or encryption techniques employed.
2.2.2.5 Specification Review
T h e last and most important step is to review the proposed system specification with all users. O n c e
again, begin at the point of origin and trace the system through to the end of processing. At each step,
identify for each user where the information required for the performance of the task will come, how
processing will take place, and how the information will be distributed subsequent to that processing step.
While time consuming, this second iteration through the system is essential. It is rare that even the most
talented, experienced system designers complete a workable system specification in o n e pass. By reviewing
the detailed system design, insight can be obtained into the design, the alternative selected, and the
advantages and disadvantages of the tradeoffs made e n r o u t e to the final design. Most importantly, the
users provide a valuable check on the design assumptions around which the successful design of the system
will depend.
2.2.3 System Selection
2.2.3.1 Survey Market
Several means exist by which a survey of commercially available C A P P systems can be made. A variety of
seminars sponsored by professional societies dealing with CAPP, G T , and related subjects are scheduled
annually and often provide an afternoon or evening in which attendees can view and discuss systems from
various suppliers. Also, tool shows and expositions often provide the opportunity to see and evaluate
various C A P P systems.
2.2.3.2 Identify Candidates
When the vendors who seem most likely to meet the needs of the business have been identified, a second
screening may be made on the basis of literature provided by each vendor. O n the basis of this review the
three or four suppliers most likely to meet the needs of the business can be identified and examined more
closely.
In order to m a k e the final determination, the field is narrowed to the two C A P P systems that most closely
meet the business needs identified in the preliminary design effort. Then the finalists are put through a
number of steps, including site surveys, sales presentations, systems analyses, technical demonstrations, and
formal proposals.
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Computer-Aided Process Planning (CAPP)
2 3 Cost Justification
Although current C A P P systems are not intelligent enough to capture all the seemingly infinite number of
variables that are associated with process planning, they are maturing and becoming more of an
economically useful tool. As these systems grow in power and sophistication, they are becoming
recognized as a "necessity" for those companies who wish to stay competitive in the future. Many large
companies have delved into C A P P and found it to be economical in spite of some limitations and costs.
As an increasing n u m b e r of larger companies use C A P P systems from a growing number of vendors, a
trend takes place that drives the cost and availability of such systems down within the grasp of medium and
small size companies.
Regardless of size, there comes a time when a company in the market for a C A P P system needs to justify
the cost of such a system. Before management commits significant dollars or resources in obtaining and
implementing a C A P P system, they want to know if the benefits will outweigh costs. For this reason two
questions need to be answered. H o w much is it going to cost, and what savings can be expected?
Questions pertaining to such things as acquisition costs of hardware, software, maintenance, training are
straight forward. These can be readily obtained from a vendor. If the C A P P system is to be developed by
the user, then software development cost, dedicated h u m a n resources, and implementation lead time are
less concrete. Capturing cost of an in-house developed system is even m o r e elusive. Some form of a
project management system is usually employed. T h e scope of work is drawn up and the resources needed
to support the work are estimated. F r o m these estimated resources a ball park figure can be arrived at for
the total system cost.
However, the question of savings becomes even more elusive than defining the cost of an in-house
developed system. Some fortunate companies have a cost tracking system that is well developed and
supported. This makes the job of estimating and tracking savings much easier. A good cost tracking
system is used as a solid standard on which savings can be based and projected. A number of companies
however, are not as advanced in their accounting methods and do not break out as many cost categories.
Thus, they struggle to find an exact cost in their existing system.
A real problem with projecting savings is to determine how much work a piece of software as complex as a
C A P P system will save in an area as all encompassing as process planning. After installation, system
performance can be measured and compared with historical data, if that data exists. In this case foresight
is needed first to justify the system.
2.3.1 System Analysis
A gas turbine engine manufacturer produces a wide variety of parts most generally characterized by
complex shapes and tight tolerances. D u e to the inherent quality and reliability requirements for aircraft
propulsion engines and the complexity of design, process plans are very lengthy, complex and meticulous.
A typical process plan ranges between 30 to 50 operations. Each operation contains machine tool used,
perishable tooling, jig and fixture tool numbers, operation description, machining dimensions and
tolerances, caution notes, specifications in a condensed form, speeds, feeds, depth of cut, and graphics.
T h e engine builder uses G T techniques. All parts are produced in o n e of four shops, namely, wheels,
gears, cases, and sheet metal. Though this is not a complete breakdown of parts into "families of parts" as
pertaining to G T it does significantly reduce the magnitude of searching needed to develop the complete
process plan as well as benefit the shop floor in facilitating production.
T h e company examined the detailed requirements for a C A P P system and defined the modules needed to
satisfy its design. Because of the interest aroused by this study, it became necessary to provide to
management as soon as possible a complete project analysis with associated costs and benefits.
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Computer-Aided Process Planning (CAPP)
A single engineer handled the analysis. T h e only other human resources dedicated were a few hours each
week of an experienced process planner.
This in-house C A P P system development was labeled C A P E (computer-aided production engineering).
Parts of the system were purchased from outside vendors, but for the most part, it is an in-house design.
C A P E is an enhanced variant process planning system, which interfaces with the existing company database
and integrates with all other departments and functions concerned with process planning.
2.3.2 Process Plan Analysis
T h e strategy used for cost analysis was simple: select a representative family of parts and develop a
standard routing for that family. Next, compare and contrast the standard routing with the existing
routings and carefully n o t e all differences. This would be followed by an analysis of those differences to see
what, if any, the cost impact would be. Lastly, the findings of the analysis would be applied to actual cost
data for a projected cost savings.
D u e to time constraints, only o n e part family was chosen for analysis. T h e family chosen was that of spur
gears with a trepan configuration. This choice was made for two reasons. First, there was an existing
classification and coding scheme in the gear shop with a significant number of the parts coded. Second, it
was felt that spur gears would be as representative a part family as the shop could offer, considering the
wide variety of part types. Seven parts fell within this spur gear family and were used for the analysis.
After the process plans were gathered, a production flow analysis was performed on the seven parts of this
family. A matrix was constructed consisting of a vertical listing of the routing; i.e., a list in descending
order of each machine tool used in the routing of the part. T h e horizontal axis of the matrix consisted of
the respective part numbers of the spur gear family. T h e matrix had to be built o n e column at a time.
Each operation for a part had to be as closely fitted and aligned to the previous part routing as possible.
This was made fairly simple, due to the great number of common operations that are a natural outcome of
G T families. T h e operation n u m b e r was placed at the intersection of each part number and machine tool.
Operation numbers are assigned sequentially, regardless of machine type or process. The load center
number which appears beside each operation takes the place of what many companies call an operation
number.
Following the matrix construction another vertical column was added. This column was a machine class or
process type column. An example of this would be calling out an operation as using a medium horizontal
N/C lathe as opposed to a specific company name and model type N/C lathe. This column was added for
use in generating a graphics flow chart of the production flow on a higher level to avoid a chart with too
much detail and clutter.
At this point, the experienced process planner was called upon to go through each routing in detail to
create a standard routing. This was a time consuming task taking o n e of the three weeks allotted to this
project. A process planner makes hundreds of calculations, judgments, and decisions to create a standard
routing. Although the seven parts of the spur gear family were nearly identical in geometry and material,
their routings differed considerably. T h e differences were because of a number of reasons, among which
were obsolete machinery, changes in methods, new equipment, different approaches and preferences of the
planner who created the routing, changes in tooling, and changes in company policy. From this careful
examination of each routing, a standard process plan was created that would cover all seven spur gears.
T h e standard routing was then compared with the matrix created earlier, and the matrix was adjusted to
reflect the standard routing. Operations were deleted, combined, and, in some cases, added to the matrix.
T h e o u t c o m e of all the changes was a decrease in the number of operations. Before the analysis, there
had been a total of 221 operations among the seven parts studied. After the standard routing was
26
Computer-Aided Process Planning (CAPP)
produced and compared, there were 201 operations among the seven parts. N/C operations were reduced
from 14 operations to nine.
For demonstration purposes and as a visual aid a flow chart was made of the spur gear family routing flow
through the shop. This simple line and circle flow diagram was used to visualize the magnitude of changes
that had taken place on the matrix. It is easier to verify a standard routing when all possible paths are laid
out for easy visual access. In addition, this chart was also used in presenting the C A P P system to
management. A network, if not too complex visually, is m o r e easily understood in a meeting atmosphere
than volumes of tabular data such as the matrix.
After the standard routing was created, the changes were transferred to the matrix. This resulted in
moving, deleting, and adding operation numbers at the intersections of the part number and the machine
or operation description. W h e n this process was finished, all vacant lines were removed. T h e analysis
discovered that a number of operations were performed in the same sequence from part to part with the
only difference being the brand name of the machine to which it was routed, which led to further
condensation of the matrix; e.g., four lines of medium horizontal N/C lathes with different manufacture
names being combined into o n e line.
2.3.3 Cost Analysis
After the estimated percentage savings were calculated, costs were gathered. Baseline cost data in this case
was from the previous calendar year for each task area. Cost data was gathered from a number of
individuals and reports. In most cases, the information was present and accurate. Only in a few instances
was a "best guess" made by an experienced person who had a good handle on the situation of that
department.
T h e collected cost information was formatted on a P C using a spreadsheet software package. T h e format
used was to group each major section; e.g., run-time, N/C, scrap. The percent of impact was calculated by
the a m o u n t that each shop spent for a particular area compared with the total for four shops.
A phasing factor was added, which took into consideration the time each shop would require to move from
the manual system to the C A P P system. T h e phasing was linear and reached 97 percent at its highest
point in anticipation that a full implementation would not be realized due to various unforeseen
conditions and circumstances. Savings for each shop were totaled as well as saving by each column or
quarter for the different areas. This pattern was repeated for each of the areas.
Implementation costs included a combination of purchased software, hardware requirements, and
personnel needed to design, implement, and maintain the total system over a period of five years. Wages
and salaries were adjusted using a six percent per year inflation factor. Net savings per quarter were
derived from the total savings less total costs. These net savings were then summed to a total net savings
over five years.
2.3.4 Savings
Substantial savings were projected from this study. A rate of return was calculated at greater than 50
percent, with the pay back occurring in the eleventh quarter. With these figures it was deemed a
worthwhile project to undertake. A presentation was made to management using these figures as well as
the graphical flow chart of the spur gear routing as mentioned earlier. T h e outcome was a general
approval of the C A P E system with further deliberation on the technical requirements of the software.
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Computer-Aided Process Planning (CAPP)
3. Manufacturing Interfaces
3.1 A Distributed, Hierarchical Architecture
3.1.1 Process P l a n n i n g
Manufacturing personnel are generally familiar with the organizational distinction between manufacturing
engineering and production control. Manufacturing engineering has responsibility to generate the process
plan. Production control has responsibility to manage the production activities, hereafter referred to as
process control. Process control is the domain where product is fabricated, assembled, tested, and
transported. It is also where the process plan is interpreted, optimized, executed, and monitored according
to specification. It is the domain of process planning to specify the manufacturing process requirements in
terms of sequence and content, and to arrange this data in a format acceptable to multiple process control
subsystems.
Process planning is positioned between product design engineering and process control of the factory floor
systems. Because the two domains share product and producibility data requirements in common, it is
compelling to merge the product design with process design. Traditionally, this has not been the case.
There is, however, a need to recognize the necessity for strong two-way integration between the two
domains to support new product startup and producibility goals. While it ultimately is a goal to
completely a u t o m a t e the generation of the process plan, this architecture does not require it. In fact, with
the wide variety and increasing introduction pace of new manufacturing process technology, the practicality
of o n e package meeting the data needs of all process control systems could likely become impossible. T h e
architecture lays the foundation upon which process planning applications can plug in or out or be implemented or replaced, as required in an integrated environment.
Currently there is little integration of shared data across factory systems. R o u t e s and bills of material are
p a r a m o u n t to the integrity and proper revision control of the manufacturing process. When a revision is
made to a process, this change should be automatically communicated to all affected systems. Currently,
manually maintained, standalone systems requiring people to run around to keep them operating is the
glue. F o r the future, manufacturing strategies must insist on integrating this reference data so that data
changed at the p r o p e r source is appropriately communicated to all affected systems automatically.
3.1.2 Architectural F u n d a m e n t a l s
O n e of the most fundamental elements of complex system design is the architecture upon which it is built.
Architecture can b e defined as many things by many people, but at the very least it describes the system
components, their interfaces, and their relationship to o n e another. Just as an architect designs the
structure before it is physically built, so does the software architect design the system architecture prior to
application development.
3.1.2.1 Interface Protocol Standards
In designing a building, the architect must adhere to certain standards, the purpose of which is to
guarantee a level of compatibility between independently designed functions that have to interface with
o n e another. A n example of two independently designed components that ultimately interface is a wall
socket and a lamp plug. Although the socket and plug perform different functions, they both have been
designed to meet the same interface standard. Because a standard exists, a radio may be plugged in
instead of a lamp without impact on the system.
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Computer-Aided Process Planning (CAPP)
Because of standards, applications may be switched in and out, and as long as they do not violate their
interface standard, the other system components are not impacted. This approach allows for flexibility in
the implementation of a system where competing modules can be selectively implemented based upon
requirements. A given application module may be replaced by another, but if the interface remains
constant, the rest of the system should not have to change.
3.1.2.2 Data Server/Database
T h e architecture is data server rather than database oriented. In a database oriented architecture, the
knowledge of the data structures have to be coded into the application. In a data server approach,
applications obtain this reference data via data management interface calls. By doing so, o n e database
product can be modified or replaced by another database product. As long as the interface call does not
change, the application will not have to change. This also can open the way to a database machine whose
sole role is to provide data storage/retrieval to any number of requesting client applications.
3.1.2.3 Function/Form
A house design is based upon the function that each room accommodates. "Kitchen" conjures a mental
picture of a cooking facility. T h e basic function of cooking will remain the same regardless of the size or
number of kitchens in the system. W h e t h e r a large stove or a small stove is requested, users know that it
goes in the kitchen and not somewhere else.
This analogous approach provides great insight into how a complex system is designed. Within process
planning, there are four basic categories of data: workflow (route), bill of material, quality, and
equipment. These categories should be as distinct and well defined as a kitchen is from the rest of the
house and understood as to their role in the process plan.
3.1.2.4 C o m m o n Support Tools
Within most systems, a common set of tools can be identified that are used throughout the system. These
tools include networking, human interface, and data management. O n e such tool used extensively within
the architecture is called the message bus. T h e use of this tool sets the stage for distributed processing
and removes the knowledge of where on the local area network the cooperating application resides. This
transparency is critical to the ability to move application modules to other computer hardware without
having to make changes to the applications making the calls.
For an application to request service, all it has to do is call the message bus and pass the list of arguments
using a predefined interface call. This would be analogous to our writing a letter (the list of arguments)
and addressing an envelope. W e do not care what the postal system does in delivering the letter, only that
it reaches its destination in a timely manner. T h e message bus takes care of physically routing the packet
of data to the appropriate destination.
3.1.2.5 Hierarchical Approach
T h e architecture assumes a hierarchical approach in positioning the process planning functions to
minimize redundancy. Plant levels such as workstation, cell, and shop can be arranged in a manner similar
to that of a traditional top-down organization chart. That is, a shop has any number of cells reporting to
it; each cell has any number of workstations reporting to it, and so on.
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Computer-Aided Process Planning (CAPP)
T h e above considerations are fundamental to the architecture discussed below. T h e architecture has made
extensive use of a protocol standards, modularity of functions, and data servers, all based on the use of a
distributed network message bus system.
3.1.3 Architectural Overview
There are three major subsystems within the process planning architecture. They are 1) the bill of
description ( B O D ) , 2) the process planning development hierarchy that is made u p of functions used to
generate the process plan, and 3) the bill of process (BOP). Data management interfaces are shown as
horizontal lines between these subsystems. Figure 11 shows this relationship. Not shown are the
command level interfaces connecting the subsystems within themselves as well as with external entities,
such as process control and product design engineering.
Business
Factory Level Generator
Bill of
Managerial
> Shop/Cednter
Functional
^Cell/Line
Data
Management Operation^
System
-Workstation
Recipe
-^Automation
Module
Shop/Center Level Generator
Description
Cell/Line Level Generator
Data
Management
System
Factory
Bill of
Process
Workstation Generator
Instruction Set Generator
PROCESS PLANNING
DEVELOPMENT
HIERARCHY
Data Input
|^
Off Line Process Development
•
On Line PD
_Process
"Controllers"
Figure 11: Architectural Overview
3.1.3.1 Bill of Description
T h e B O D is a data management system focused on management of data that is independent of any specific
process plan but may be referenced by any number of process plans. It manages relatively static data that
describes product/parts, plant resources, and general process knowledge requirements.
G T coding and classification approaches would fall within this domain. Notice that this data remains
constant and does not change unless there is a change in product design, plant resource, or manufacturing
strategy.
3.1.3.1.1 Part
Product data must be provided by design engineering in a state acceptable to manufacturing. This requires
an interface to the C A D systems, commonly referred to as the C A D / C A M interface. This includes part
master and manufacturing bill of material (BOM).
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Computer-Aided Process Planning (CAPP)
3.1.3.1.2 Plant
Plant data is owned primarily by manufacturing. It describes the resource capabilities, capacities,
configuration, and control hierarchy of each plant entity. Data owned by finance systems, but considered
to be plant data, are master data tables such as operation codes and employee identification numbers.
Plant data is used by a number of systems including process modeling/simulation, short interval scheduling,
capacity resource planning in M R P II, as well as other process control systems.
3.1.3.1.3 Process Knowledge
Process knowledge is a grouping that represents the rules, knowledge, and strategies that are used to
generate/develop a process plan. T h e process rules are general in nature in that they may apply to any
number of process plans and are therefore specific to a process in a global sense as opposed to a specific
process plan. Only as the manufacturing process strategy changes do the process rules have to be
modified.
3.1.3.1.4 Data Management Interfaces
Referring to the B O D in Figure 11, are two sets of data management interfaces. The interface
diagrammed to the left is used to maintain the B O D data. This interface set supports a full range of
database manipulation capabilities including creation, modification, and deletion of data. The functions
responsible for maintaining this data can be either front-end terminal screen-based programs that retrieve
and modify the data, or some other on-line data management system that uses this interface set to load the
data into the B O D . However, the most desirable option when dealing with another on-line system is to
place data servers on that data source thereby effectively integrating that system into the larger B O D data
management system environment.
Regardless of the source of the data, any application can make data management queries conform to the
protocol interface specification. This is the set of interfaces extending out of the B O D and into the
process planning functions. As denoted by the o n e way flow of data, these support read-only data access.
This guarantees that the data can only be changed by the originating source of that data. Therefore, the
modify and delete interface calls are not allowed for use by the process planning function.
3.1.3.2 T h e Development Hierarchy
T h e primary responsibility of this subsystem is to generate a cost effective process plan that meets the
product and process specifications as defined in the B O D . In a traditional sense, the process engineer has
to interpret the product specifications, understand the process resources available, and, drawing from
previous experience and process knowledge, generate the process plan.
Before the plan can be released, it must be verified and approved. T o verify a plan may involve process
simulations against a specific o r average product load using varying resource allocations. Verification may
also take place to assure that all recipe programs are syntactically correct and that the data is of the
correct format and meets the data requirements of the various process control systems.
3.1.3.2.1 Hierarchy
Different types of data requirements can be seen in Figure 11, depicting five levels of a production facility.
Business data refers to the level of process plan data that plant wide systems such as M R P II would
require. Managerial data refers to the level of data that is required by shop level subsystems to optimize,
32
Computer-Aided Process Planning (CAPP)
execute, and monitor production tasks across a process line. Functional data refers to the process plan
requirements of the cell/line controller to specify the activities to be executed by its workstations.
Operational data describes the coordination activities within the workstation. T h e recipe data provides the
predefined sequence of activities required by an automation module.
T h e difference between on-line and off-line underscores the distinction between creation of the process
plan and the access of this reference data by process control. T h e process planning components that
create the process plan data are commonly referred to as generators; e.g. instruction set, workstation,
cell/line, shop/center, or factory generators.
T h e automation module level is the level in process control that the instruction set generation addresses.
T h e instruction set generator is probably the best understood component in the hierarchy. T h e output of
instruction set generators are known as N/C programs, patterns, scripts, pick and place programs, automated test programs, vision programs, and instruction sets for human operators. T h e major responsibility of
the instruction set generator is to arrange the automation module program instructions into an optimal
order, given the input limitations provided from its workstation generator.
For an instruction set generator to generate a program, it requires a data management interface to the
B O D for product and standard set up information; and a data management interface to the B O P for
contextual process plan development information such as setup requirements/restrictions and the specific
component parts involved in the step. It also requires a command via the command level interface from
its higher level workstation generator to initiate the data management interface calls and begin the
instruction set development activity.
T h e responsibility of the workstation generator is to manage the instruction sets generated by its
instruction set generators as well as provide operating data such as state tables, which the workstation
controller requires. T h e workstation generator understands the relationships that exist between the
workstations and their automation modules.
Each of the cell/line, shop/center, and factory generators perform the same type of responsibilities that the
workstation generator performs. However, each generator addresses the data requirements appropriate at
its own level. Each level has the capability of receiving and responding to high level commands, making
decisions within the command limits allowed, and assigning and monitoring process planning tasks at its
lower level.
T h e exchange of data between any two generators is termed as the command interface protocol. The
generator that originates the command is the source and is at a higher level in the hierarchy than the
commanded generator. Commands travel downwards and command responses are returned upwards.
Therefore, commands travel vertically within the hierarchy whereas data management interface protocols
travel horizontally. T h e types of data addressed by the command interface are:
•
the part number of the part being built
•
the material/components involved in the activity
•
the equipment configuration (set-up) requirements
•
a unique tag identifying the specific output process plan data so that subsequent
communication between any two generators is guaranteed
Efforts continue on standardizing process control command level interfaces. T h e manufacturing message
specification (MMS) is o n e such standard that, although targeted for relatively unintelligent devices,
provides the command interface protocol concepts required for communication between process planning
generators.
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Computer-Aided Process Planning (CAPP)
3.1.3.2.2 Categories of Data
A n analysis of the data needs of the process control system highlights four basic categories of d a t a workflow (route), material, quality, and equipment. These categories of data are found replicated within
the hierarchy as often as the data is required by process control, based to greater or lesser degree upon the
need of the corresponding process controller. T h e process planning functions required to generate this
data will exist at the same level that the data is required.
In process control, the workflow controller optimizes the production build schedule through use of short
interval scheduling (simulation) techniques. This optimized list becomes input into an execution controller
that controls the workflow based on run time status. A monitor controller compares the theoretical
optimized schedule against the actual load status and makes a determination of when to take corrective
actions including regenerating a n o t h e r optimum build schedule.
T h e workflow generator in process planning must take the data needs of each of these workflow
subsystems into account when it is generating the process plan. Typically, the data needs of the
optimization controller are different from the needs of the execution controller; and the needs of the
monitor are vastly different from the needs of the other two subfunctions, even though all three have some
of the same data needs in common.
O n e c o m m o n data thread across most process control workflow subsystems is the need of routing
information. The workflow generator must be able to generate o n e logically consistent route definition
across multiple subsystems, while meeting the independent data needs of each of these workflow
subsystems. T h e route definition should also be able to support the branching logic for rework and other
alternate next step scenarios, and arrange this in a hierarchical manner consistent with the way process
control expects to assign the process plan to its process control hierarchy of controllers.
Once the workflow is defined, the three other functional categories of data can be developed and
associated to a specific point within the workflow definition. T h e material generator working off of the
route definition determines the consumption p o i n t - s o m e t i m e s called an operation or s t e p - o f every
component part listed on the manufacturing B O M . T h e quality generator must provide the data necessary
for process control to monitor the process and to determine what, if any, action should be taken to resolve
an unacceptable quality problem. T h e equipment generator among other things specifies the number and
type of tools required to perform the task, the tool wear characteristics-used by process control to track
preventive maintenance criteria, and the recipe data required by the technology dependent automation
modules.
3.1.3.3 B O P Data Management Systems
T h e B O P data management system maintains the process plan data generated by the process planning
generator functions. It is a logical data management system in that the data may very well be physically
stored closest to its ultimate point of use. T h e approach taken recognizes that workflow (route) definition
provides the framework upon which all other process plan data is associated. When a point in the route is
established, o n e can begin to associate detail data that helps describe the activity at that process point.
As such, the B O P must be capable of modeling a hierarchical route where a route step at o n e level can
explode into a subroute composed of a set of steps describing the lower level route requirements. As
shown in Figure 11, each level within the B O P hierarchy addresses its own level of process plan detail
data.
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Computer-Aided Process Planning (CAPP)
Once a step in a route has been defined, attribute data can be associated to that step by the use of "views."
A view defines some a m o u n t of data that describes what is to be done by a subsystem at a step. If it were
a transport system, then the data associated to the step will be of the content and format useful to the
transport controller to execute its requirement. A n o t h e r subsystem may be involved in the same step but
for a different purpose; e.g., the M R P system that is tracking work in process and labor would require a
different set of data that would describe the step requirements in the content and format acceptable to
MRP.
View data can be of any content and format required by a workflow optimizer, workflow execution module,
workflow monitor, material controller, quality controller, or equipment controllers, including route step
data, a recipe, a list of tools required, fixtures, graphical/textual work instructions, and data collection
requirements. Giving a group of data a view n a m e provides a way to store and retrieve process plan data.
It can be stored and accessed by referencing the view n a m e of the step in question.
3.1.3.3.1 Data Management Interface
Because of the need to appropriately model the various subsystem views of data and represent it
hierarchically, a general interface to read and write process plan data to and from t h e B O P data
management system has been devised. The B O P has two sets of clients. Internal clients, such as process
planning generators, have read/write access because of their role in the generation of the process plan.
External clients, such as process control, have read-only access since their role is to execute the process
plan.
There are four basic read-only call interfaces used typically by process control subsystems to obtain route
and other workflow related data. G E T _ R O U T E is generally used when the route data is batch loaded as a
private route copy into a n o t h e r subsystem. This might be d o n e to download a workcell route to a vendor
specific F M S subsystem. If this were the case, then "FMS" could be the view n a m e and the group of data
required by the F M S could be retrieved by G E T _ R O U T E .
A run time interactive scenario is also supported when process control subsystems request route data on a
step by step basis, as each step is completed. R u n time requests use G E T _ F I R S T _ S T E P ,
G E T _ A L L _ N E X T _ S T E P S , and G E T _ N E X T _ S T E P . This approach frees up the requirement of the
subsystem to maintain a local private representation of its routing requirements and puts the data caching
back into the hands of the B O P data management system.
T h e same approach can be taken to define the interface calls that support the process planning generators'
ability to create, modify, and delete B O P data.
3.1.4 Integration to External Architectures
As important as it is to have a well structured process planning architecture, strong integration must also
exist with the product design architecture. Figure 12 highlights how this integration can occur by use of
the message bus.
At the top of Figure 12 is a series of interfaces to external architectures such as product design
engineering, order transaction processing (for job shop/customer order specific requirements),
producibility, process control, and other systems/functions external to the process planning architecture.
Each of these architectures must be tied into the message bus using an agreed upon set of interfaces, thus
achieving a closed loop system. T h e formats of these interfaces need to be general in nature because they
are expected to support a wide variety of data transmission requirements.
Use of the message bus allows for a distributed environment where generators can b e scattered throughout
35
Computer-Aided Process Planning (CAPP)
Product
Design
Engineering
τ
Annotated
Product
Data
Product
Data
Producability
Order
Transaction
Prooessing
Process
Control
τ
Process Planning Interface Message Bus
Product
ECO/ECR
Change
Notification
Process
ECO/ECR
Change
Notification
Process
Plan
Detail
Data
Customer
Order
Rqmts
1
Bill of
Description
(BOD)
1
Process Planning
Generators
Bill of
Process
(BOP)
Figure 12: Process Planning External Architecture
the network. And because this generally means distributed databases, a basic problem involves keeping the
system updated to the most current information. That problem is solved in the process planning architecture, as data is changed by o n e subsystem, notification of that change is "broadcast" via the message bus to
all affected systems.
The message bus is a utility which guarantees delivery of the broadcasted message to any subsystem which
has previously registered itself as an interested party for a particular broadcast message type. The
broadcast message can contain all of the data associated with the change, or it can contain pointers that
map back to the change data.
In the first scenario, the message is looked upon as a "push" of data to the subsystem. Generally this
approach is used when the content of data is minimal. On the other hand, if the content of the data is
great, then a "pull" approach may be preferred which gives the individual subsystems the ability to request
the changed data at some convenient future moment.
T h e pull approach is used in the process planning architecture to obtain product description data from
design engineering architectures as well as customer order information from order transaction processing
systems. A notification of E C O / E C R (engineering order/change) product data is received as a "pull". This
means that the detail product data is not passed as part of the notification message but is subsequently
pulled into the B O D which manages among other data, the raw product detail data.
Once product data is in the B O D , it is checked for completeness. If the data is found lacking, then a
subsequent unacceptable broadcast can be made back to the C A D / C A E source requesting the
modifications to be made. If it is extremely critical due to time or cost constraints, then it may be
annotated as long as the annotated product data is broadcast back to the true source/owner of that data,
the product design engineering community.
36
Computer-Aided Process Planning (CAPP)
T h e process planning generators then perform their value added functions by merging the B O D data into a
consistent process plan. T h e process plan data is physically stored and managed by the B O P data
management system. O n c e the process plan is complete, notification that the process plan has been
released is broadcast via the message bus. Any interested party can then retrieve the released process plan
data via the message bus using the standard data server interface calls supported by the BOP.
3J2 An Integrated Scheduling System
3.2.1 System Overview
A n automatic C A P P system based on G T concepts has been developed and combined with a group
scheduling algorithm called key machine loading (KML) to form an integrated computer-aided process
planning and scheduling system (ICAPPS). New concepts, like part machining surface set (PMSS) and cell
machining surface set (CMSS) proved effective in combining the automatic process plan generation with
GT. T h e K M L algorithm guarantees no-idle time for key machine tool and minimum lead time for the
job. T h e integration of C A P P and scheduling is accomplished through the use of the cell machine loading
and alternatives algorithm (CMLA) and scheduling source file (SSFL). This allows the system to modify
the process plan automatically and thus, to avoid possible conflicts when changes in j o b orders and
machine tool allocations occur.
3.2.2 CAPP and the Process Plan
Generally, C A P P and scheduling algorithm are performed separately. And yet such an integration is
necessary, if modification of the process plan due to scheduling conflicts is to be carried by the system.
This, in turn, would lead to the increased efficiency of those two important functions linking C A D and
CAM. T h e task of integration is a difficult one, judging even from the fact that process planning is
concerned with technical requirements, while scheduling is concerned with the time factors.
In practice, modification of the process plan sheet is routinely necessary, because of the need to utilize
alternative machine tools. This happens either because of overloading or breaking down of some machines
or because of changes occurring in the job orders. An automatic search for the most appropriate
alternative machine tool and subsequent modification of the process plan constitutes the rationale for the
development of an integrated system. T h e automatic process planning generation is combined in this
system with G T concepts as are some other new approaches.
3.2.3 ICAPPS Subsystems
As can be seen from the block diagram in Figure 13, the ICAPPS system consists of three main
subsystems:
•
•
•
the process planning generator
the key machine loading algorithm
the operation planner
T h e C A D database is a common database used by C A D and CAPP. A small database is established to
store part geometry data and technical requirements. T h e boundary representation of the solid geometry
model is chosen to describe the parts. In the boundary m o d e l a face is defined by a list of edges, each
edge being represented by two vertices. This is a general rule; in a real system, some special faces can be
defined by conventional rules.
37
Computer-Aided Process Planning (CAPP)
Design
CAD
I
Geometric
Model
Technical
Drawing
Technical
1 Files
1
f
PPG
PMSS Generator
ψ
CMTT File
—>•
CDB
Machining Sequence
and
SSFL Generator
>
<
CMSS Files
PAEK Rules
1
KML
Algorithm
Fixtures
Tool Files
Operation
Planner
CNC Tape
Files
CDB
Process Plan Sheet
and Job Order
PPG
PMSS
CMSS
SSFL
PAEK
KML
CMTT
CMLA
CDB
-
Process Planning Generator
Part Machining Surface Set
Cell Machining Surface Set
Scheduling Source File
Production Axioms and Experience Knowledge
Key Machine Loading Algorithm
Cell Machine Tool Table
Cell Machine Loading & Alternatives
Cutting Data Base
Figure 13: ICAPPS System
Technical requirements can b e divided into the index data and technical data.
Index data contains indices
of brief information about all faces to be generated, such as shapes and surface roughness.
It is easier to
extract all faces by using t h e index data than by comparing the part geometry data with its blank data.
Therefore, it would be advantageous to use t h e index data when a part and its blank a r e complicated.
38
Computer-Aided Process Planning (CAPP)
3.2.3.1 T h e Process Planning G e n e r a t o r ( P P G )
T h e functions of the P P G are:
•
to extract faces from the boundary model and to integrate them into the PMSS
•
to compare the PMSS with the CMSS to find the best group of machine tools
•
to generate an approximately optimum machining sequence based on AI techniques and
optimization criteria
•
to estimate the machining time for parts on every machine tool and to produce a scheduling
source file
T h e P P G obtains information from the data files, and functions as described below.
3.2.3.1.1 T h e Part Machining Surface Set (PMSS)
The PMSS is a set of surfaces to be generated through machining in the order which is arranged according
to certain rules. Every machining surface or element of the PMSS is expressed by the shape symbol, size,
and necessary technical data. The PMSS provides all essential information of a part for process planning.
T h e technical requirements are represented by the accuracy and surface roughness. T h e r e can be the
accuracy of size, shape, or position. T h e level of the accuracy-high or e c o n o m i c a l - d e p e n d s on the actual
situation in the job shop.
There are two rules for arranging the order of PMSSs for rotary parts: from left to right for external
surfaces and from right to left for internal ones. For prismatic parts, the rule is from the datum plane to
the top plane, with holes and slots included between the planes. Through the extension and combination
of these rules more complicated PMSS can be arranged.
3.2.3.1.2 T h e Cell Machining Surface Set (CMSS)
T h e CMSS is a set of preselected surfaces which can be machined by a group of machine tools. In a job
shop, only a part of the functions of a machine tool is used. T h e machining operation is related to tools,
fixtures, and attachments. It is necessary to consider them when analyzing the shape generation on
machine tools in the process of selecting a set of feasible surfaces to be generated by a cell. This set of
surfaces forms a CMSS. T h e main parameters used to represent the CMSS are similar to those used in
PMSS.
3.2.3.1.3 Extracting Generated Surfaces
T h e process of extracting surfaces to be generated is shown in Figure 14. At first, all faces to be
generated are extracted from the part geometry model, then they are integrated into the geometry
description of machining surfaces ( G D M S ) according to integration rules. O n c e G D M S is formed, it will
be combined with technical data to form a machining surface. Finally, by repeating this process, the PMSS
is generated.
39
Computer-Aided Process Planning (CAPP)
Extract all faces to be
generated according to
the index data
Data file for all faces
to be generated
Integr.
Rules
technical data to form a
machining surface
ι
End
Figure 14: Extracting Generated Surfaces
3.2.3.1.4 Finding the Best Cell
Generally, cells can be divided into two kinds: that for machining rotary parts and that for prismatic parts.
When a part can be machined in o n e cell, this cell is the best choice. In order to find the best cell, the
PMSS is compared with the CMSS. If the PMSS is included in the CMSSX (X is the cell number), then
the CMSSX is the best cell. If n o n e of the CMSS can include the PMSS, the CMSSY, which can include
most of the elements of the PMSS and requires the minimum number of additional machine tools to
complete this part, is the best cell. T h e next cell is selected on the basis of a neighbor principle.
3.2.3.1.5 Production Axioms and Experience Knowledge (PAEK)
T h e production axioms are logical and general concepts and can be used to make logical inference. They
are the result of analysis of shape generation process on machine tools and methods implemented to
guarantee part requirements. These production axioms are adapted to any job shop manufacturing system
except for some special cases. T h e production axioms concern:
•
the shapes of surfaces and corresponding machining methods and machine tools
•
some fixed machining sequences for generating surfaces
40
Computer-Aided Process Planning (CAPP)
T h e experience knowledge usually deals with a particular manufacturing system and with the performance
of an individual machine tool. It can be applied to:
•
shapes of surfaces and corresponding individual machine tool
•
typical machining sequence for a surface in a particular manufacturing system
•
other constraints (tools, fixtures...)
3.2.3.1.6 Cell Machine Tool Table (CMTT) and Cutting Database (CDB)
T h e C M T T is used for selecting the best machine tool from the point of view of the best manufacturing
performance. In order to create this file certain rules and criteria have to be established. T h e data for
C D B comes from industrial practice.
3.2.3.1.7 Machining Sequence Generation
The information obtained from the data files is used to generate the machining sequence. For this
purpose AI techniques and optimization criteria are applied. AI techniques involve backtrack search
strategy and production rules which are based on the production axioms and experience (expert
knowledge), which are used to select the machining sequence of some surfaces. After this step, there are
generally several surfaces left in the parts, which need to be machined. Optimization criteria is used to
minimize machining time of the remaining surfaces. This criteria depends on a number of factors,
including total length of a part, average diameter, width, cutting length, cutting speed, feed rate, and
material.
Some of these factors can b e treated as the main factors. In this system, the cutting depth, d, and the
cutting length, 1, are considered as the two main factors. According to the variations in d and 1, several
machining sequences can be produced, from which the best o n e can then be selected.
T h e procedure of process planning can be divided into two steps. T h e first step deals with the surfaces
which require high accuracy and low surface roughness. T h e second deals with those whose accuracy and
roughness are economical to achieve. Every step has many substeps which vary from rotary parts to
prismatic parts.
T h e process planning generator will estimate the machining time on every machine tool on the basis of the
similar principle and will produce a data file called scheduling source file (SSFL) for scheduling. T h e
estimation depends mainly on the experimental data in a job shop. A n example is shown in Figure 15.
3.2.3.2 Key Machine Loading Algorithm (KML)
Generally, a load unbalance exists among a group of machine tools. A machine tool loaded more than
others is called the key machine tool (KMT). T h e K M T with no idle time might ensure increased
productivity in some cases. T h e K M L algorithm is based on this idea and is constructed to guarantee that
key machines have n o idle time and the job can be completed on due date under a minimum lead time
when batch jobs are scheduled among a group of machines.
T h e K M L algorithm uses the C M L A file. This is an important file for integration of C A P P and
scheduling. This file gives information regarding job starting time and completion time, machine loading,
and alternatives. T h e modification of the process plan sheet depends on this file.
41
Computer-Aided Process Planning (CAPP)
i
PMSS Files
I
Compare PMSS with CMSS
Determine The Best Cell
CMSS
Files
I
Select Finishing Methods and
corresponding MT
Select Allowance
I
Determine Optimum MQ
Select Economic Methods and
Corresponding MT
CDB
I
Estimate Machining Time on
Every MT
CMTT
I
Primary Process Plan Files
Scheduling Source File
Blank
Data
MQ - Machinging Sequence
MT - Machine Tool
Figure 15: Flow Chart of Process Planning
Jobs can be ordered based on the priorities fixed according to the due date. A batch of jobs is set on the
same due date. In the batch job case with K M T as the first machine in a group, the K M L algorithm
minimizes the total flow time T f , then calculates the minimum lead time T m which is given by
T m = T f - T p,
where Τ
is a certain time period.
42
Computer-Aided Process Planning (CAPP)
If T m is negative, no lead time is necessary.
In cases when K M T is not the first machine, after the algorithm minimizes flow time T f , the minimum
operation time T k m which guarantees that K M T has no idle time, is calculated along with the new
completion time for all jobs. T h e new minimum lead time T m is then calculated:
T m = T k m + ( T c - T p) ,
where T c is the last job completion time on the last machine.
When scheduling random jobs among cells, K M L uses a dispatch rule called FCFS-A, where A means
alternative. In this case, the algorithm deals with two problems:
•
scheduling jobs among all cells if some machine have enough idle time
•
cancelling some jobs in order to insert some urgent jobs
3.2.3.3 T h e Operation Planner
T h e Operation Planner has the following functions:
•
selecting cutting speed and feed rate and calculating machining time
•
modifying "machine loading table
•
selecting tools and fixtures
•
printing the process plan sheet and job orders
•
producing C N C tape file
43
Computer-Aided Process Planning (CAPP)
4. Applications
4.1 Machined Cylindrical Metal Parts
C o m p u t e r managed process planning (CMPP) is an advanced process planning system for machined
cylindrical parts. While C M P P is a partial implementation of C A P P technology, the concept can be
extended to other applications.
C A P P typically addresses up to four process planning functions: sequence of operations, tolerance control,
reference surface selection, and process plan output. C M P P is a generative system that addresses all four
functions. It is unique due to the fact that the software and complete documentation are available to U.S.
companies and government organizations at no cost.
4.1.1 Characteristics
The characteristics of C M P P are:
•
G e n e r a t i v e - I t develops process plans rather than simply recording o p e r a t o r decisions.
•
Interactive-Interactive changes to the process plan can be made by a process planner, if
desired.
•
Manufacturer I n d e p e n d e n t - I t is not dependent upon any o n e manufacturing process
philosophy. It can be used by different manufacturers on different type parts.
•
Process Decision Models U s e d - U s e r dependent process decision models, written in an
English-like language that is understood by the system, provide manufacturing logic for part
families.
•
C o m p u t e r Part Modeling U s e d - A process plan is developed, operation by operation, to
transition the raw material into a finished part based on a detailed description of the part and
raw material.
4.1.2 Geometric Coverage
C M P P concentrates o n the capability to deal with cylindrical surfaces and features. However, some
noncylindrical features are also handled, but less completely than the basic cylindrical geometry.
•
Cylindrical S u r f a c e s - T h e system handles diameters, faces, tapers, and circular arcs
•
Cylindrical F e a t u r e s - F e a t u r e s such as grooves, recesses, reliefs, and notches are supported
•
Non-cylindrical F e a t u r e s - O t h e r features such as holes, gear teeth, windows, flat slots, and
splines are also supported along with functions such as heat treating and surface finishing
45
Computer-Aided Process Planning (CAPP)
4.1.3 C M P P Major Components
Functionally, C M P P uses four input sources and provides three outputs (Figure 16). The inputs are: part
data, process decision models, machine tool data, and user interactive instructions. T h e system outputs a
routing sheet, dimensioned operations sketches, and a tolerance chart.
Machine
jData
Process Decision
Models!
Part
Data"
Computer Managed
Process Planning
(CMPP)
Routing Sheets
— •
•
Tolerance
Chart
Dimensioned
Operation
Sketches
User
Figure 16: Functional View of C M P P
C M P P Software is composed of three major components: database system, part input system, and
processing planning system (Figure 17). It performs four functions: generates a summary of operation;
selects surfaces for dimensioning references, clamping and locating; calculates machining dimensions and
tolerances; and outputs process documentation. The database and part input systems are not strictly
process planning components but are necessary in order to plan a process. T h e components of and
functions accomplished by the software are described in the following paragraphs.
Figure 17: Major CMPP Components
4.1.3.1 Database System
The database system provides the manufacturer independence for CMPP. It builds local files of user
dependent manufacturing logic and parameters. As shown in Figure 18, it consists of four files.
•
T h e Manufacturing Vocabulary File lists the local manufacturing vocabulary terms that may be
used to process decision models. It is composed of the English-like description of each term.
46
Computer-Aided Process Planning (CAPP)
•
T h e Machine Tool File lists the machine classes and individual machine tools within each
machine class of the user's workshop.
•
T h e Cut Parameter File contains data on the machine tools' metal removal and tolerance
holding capabilities.
•
T h e Process Decision Model File contains local manufacturing logic. A process decision
model states manufacturing rationale for determining the sequence of operations of a part.
A n English-like, problem oriented Computer Process Planning Language ( C O P P L ) is used to
define manufacturing practice for families of parts. However, the system does not require a
specific G T coding system for part families. C O P P L process decision models are compiled
into CMPP-executable form, stored in the database, and executed for individual parts during
process planning. T h e C O P P L language uses an open-ended vocabulary of manufacturing
terms. This vocabulary can be extended to include terms required by a particular user. Each
vocabulary term has a "definition" which is understood by the process planning system.
Define
Vocabulary
Compile Process
Decision Models
^
PROCESS
PLANNING
Build Machine
Tool File
SYSTEM
ι
•
Build Cut
Parameter File
Figure 18: Data Base System
4.1.3.2 Part Input System
T h e part input system (Figure 19) receives part data and constructs computer models for use in process
planning. Part data input is a three-step process: initial part data collection, part data editing (data can
be completed or changed), and generation of an internal C M P P part model from edited part data.
Each model is a detailed description of a part and the raw material from which it is fabricated. T h e model
describes each surface, feature, dimension, tolerance, and notes. T h e system is designed for interactive
part data input, so that it can be used as a standalone system. However, it can also be interfaced with a
C A D engineering database for greater effectiveness.
47
Computer-Aided Process Planning (CAPP)
Collect
Part Data
Edit
Part Data
Build
Part Model
PROCESS
-PLANNING
SYSTEM
Figure 19: Part Input System
4.1.3.3 Process Planning System
The process planning system (Figure 20) applies the manufacturing practices and resources defined in
C M P P to a part to produce a process plan. The four technical functions are a summary of operations,
reference surfaces, stock removal analysis, and process data.
Generate
Summary of
Operations
1
Select
Reference
Surfaces
Calculate
Dimensions &
Tolerances
Output
Process
Data
Figure 20: Process Planning System
48
Computer-Aided Process P l a n n i n g (CAPP)
•
A Summary of Operations is generated by executing a process decision model. T h e model
determines the operations in sequence. Operation description, machine type, setup
orientation, and list of cut surfaces are generated for each operation. A summary of
operations can also be produced without a process decision model by interactively specifying
each operation. T h e summary of operations is presented in a matrix format so that each
horizontal line describes the operation, machine, and surfaces/features affected. Each vertical
line designates the manufacturing steps which produce an individual surface or feature of the
part.
•
Reference Surfaces are determined after the summary of operations has been generated.
Surface selection for dimension reference, clamping, and locating for each machining
operation is provided by execution of decision models or interactively.
•
Dimension, Tolerance, and Stock Removal Analysis is performed as the third step. An initial
starting tolerance is assigned to each cut and tolerance accumulations are calculated. When
necessary, these tolerances are selectively tightened to meet tolerance requirements. This
adjustment is made by a sophisticated algorithm with the objective of optimizing tolerance
capabilities of shop equipment. Toleranced stock removals are then calculated, based on raw
material tolerances, machining tolerances, and stock removal capabilities of machine tools.
Potential problems of insufficient stock removal are diagnosed and flagged for interactive
resolution during this step. Finally, nominal stock removals are used to c o m p u t e nominal
machining dimensions for each cut.
•
Process Data, the final output, includes a printed routing sheet or sequence of operations and
operation sketches, and tabular tolerance charts. T h e sketch is a not-to-scale drawing of the
workpiece with cut surfaces highlighted by heavy lines. Surfaces not yet formed are shown as
dashed lines inside the workpiece outline. Toleranced machining dimensions for cuts in the
operation are included on the sketch.
4.1.4 CAD/CMPP/CAM Integration
Although designed to o p e r a t e as a standalone system, C M P P achieves maximum advantage when
integrated into a C A D / C A M system. Use of part data from an engineering database; o u t p u t of process
documents to a graphics system; and use of o u t p u t data for tool design, N/C programming, and other
manufacturing services maximizes its usefulness. Thus, C M P P offers benefits in process planning, other
manufacturing services, and t h e shop. Case studies and estimates indicate cost savings of 25-45 percent on
process planning labor depending on the extent of use. Savings in other manufacturing services depend on
the extent of use of the o u t p u t data. Savings on the shop floor are the result of improved and
standardized process plans. Although the percentage of savings is greater for process planning, total dollar
savings may be greater in the other areas, due to their greater cost. Savings are especially significant when
complex parts fabricated from expensive materials are produced.
4.1.5 Field Testing a n d Implementation
C M P P was field tested by three aerospace companies during the development process. Benefits verified in
process planning include labor savings, lead time reduction, and surge capability. Savings of 25-45 percent
are indicated, depending on whether it is implemented during low rate production or at full-scale
production. This is consistent with surveys and studies of expected savings. N o experience data is yet
available on savings from manufacturing services on the shop floor. T h e survey and studies indicate that
full integration would result in substantial dollar savings, although the percentage would be smaller than
for the process planning function.
49
Computer-Aided Process Planning (CAPP)
Implementation of C M P P requires the commitment of top management, since it involves a radical change
in the way of doing business and a significant investment in funds to develop the local database. C M P P
users have found useful applications for portions of the technology, such as the tolerance module. Partial
implementation in a variety of industries has been reported, including jet engine, control system
components, gears, bearings, electric motors, petroleum, cutting tools, and electro-optical components.
Initially, C M P P was demonstrated o n IBM and U N I V A C computers with Tectronix terminal and CalComp
plotter. U s e of C M P P on any o t h e r equipment required modification of the software. T h e capability to
interface with C A D was demonstrated, but was not part of the delivered software; however, ease of
implementation has been and is being addressed.
A contract was awarded to modify C M P P for application on Digital E q u i p m e n t Corporation's ( D E C )
V A X computers. Additionally, neutral input and output interface will be implemented by the use of DI3000 graphics software. These enhancements increase the transportability and reduce the implementation
cost of C M P P .
4.2 Printed Circuit Board Assembly
CAPP systems today are either highly domain specific; i.e., deal with a specific technology or
processes, or are shells that become highly domain specific when implemented. This reflects
the underlying theory is inadequate to unify, in a practical manner, the diverse environments
manufacturing. Until this theory is better developed, C A P P systems will remain very domain
set of
the fact that
that exist in
specific.
Interest in C A P P is also shown by the increasing number of commercially marketed software packages that
are designed to assist in manufacturing planning. In addition to helping construct a process plan, some of
these systems help in the production of shop aids, postprocessor instruction sets, and test routines.
Moreover, several firms in military electronics have constructed rather elaborate C A P P systems to meet,
among o t h e r things, a need for exhaustive, traceable documentation of the process used on each and every
copy of a product produced. Indeed, any firm producing electronics which must be supported in the field
over a period of years, needs to know the production process that was used to manufacture individual units
so that decisions dealing with recall and modification can be made in the most economical manner.
4.2.1 The P/CB Assembly Task
T h e specific planning task that occurs in the manufacture of electronic equipment concerns the attachment
of components to a P/CB. It is also referred to as P/CB assembly or "populating the board."
In comparison to metalworking and many other manufacturing processes, circuit board assembly is a
relatively simple process. O n e begins with a bare P/CB and attaches to it various types of mechanical and
electrical components and subassemblies. While some components are mechanically attached, most are
first temporarily affixed to the board by inserting the leads of the components into holes drilled in the
board or by the use of adhesives. T h e attachment is made permanent by a soldering operation that can
take various forms depending on the type of component that is to be attached. T h e soldering operation
must also provide the connections required to make the circuits o n the board electrically functional. The
bare P/CB can be viewed as a component itself.
T h e process of attachment can b e accomplished manually, by robot, or by a variety of auto-insertion
machines that are dedicated to the insertion of particular types of components. T h e first step in the
planning task is the selection of an appropriate attachment process. This selection is determined by the
geometry of the part to be attached, the proximity of the part to other parts on the board, and a variety of
thermal, chemical, electrical, and material handling considerations. While machine attachment generally
50
Computer-Aided Process Planning (CAPP)
produces higher yields than manual attachment, not all components can be economically attached by
machine. Moreover, the economics of production require that some components be attached manually,
even though they feasibly could be auto-inserted or inserted by robot.
In short, the process starts with a bare P/CB and a collection of electrical and mechanical components.
T h e problem is to specify the manner in which each component will be attached to the circuit board.
4.2.1.1 Order of Operations
T h e general flow of work is shown in Figure 21 and proceeds as follows:
TEMPORARY
Clinching
Wax
Manual
Robotic
Fixed Automata
Manual
Robotic
Fixed Automata
Pre-attachment
Operations
Attach Certain
Mechanical
Components
ATTACHMENT
Flux
Adhesive
/
VCD
Dip Machine
Machine
Axial
Component
Insertion
Dip
Insertion
Manual/Robotic
Insertions
of other
Components
Perform] Leads
Coat
TYPICAL COMPONENTS
Tin
Solder
Latches and other mechanical assemblies
Labels
Single in-line packages (SIPs)
Dual in-line packages (DIPs)
Radial components
Axial components
Cans
"J" packs
Leaderiess chip carriers (LCCs)
Connectors
Chips
Rat packs
Heat sinks
Sockets
LED and optical displays
Post-solder
Attachments
Have
Vapor
Phase
Laser
LR.
Hand
Solder
Test
SUPPLIED
Bulk or loose
Reel
Tube
Magazine
Carrier
Figure 2 1 : Typical Steps in the Assembly of a P/CB
(1)
Preassembly operations on components for purposes of trimming and forming leads and other
modifications to vendor supplied components.
(2)
Attachment of certain mechanical components by hand, robot, or fixed automation device.
(3)
Insertion of dual in-line packages (DIPs) by DIP auto-insertion machines.
51
Computer-Aided Process Planning (CAPP)
(4)
Insertion of axial components by variable center distance ( V C D ) machines. An axial component is
o n e whose leads pass axially through the normally cylindrically shaped components; e.g., a typical
resistor.
(5)
Manual or machine insertion of radial and other components as well as axials and DIPs, which for
o n e reason or another could not be machine-inserted during earlier steps. A radial component is
o n e whose leads extend radially out from a circular shaped body such as a disk capacitor.
(6)
Soldering.
(7)
A final hand or robotic assembly work center for attaching components that cannot be soldered or
components that, because of size, shape, or location must be attached and soldered after all others
have been attached and soldered.
(8)
Test.
In the case of boards that involve surface mount devices (SMDs), the processing steps are slightly
modified. Machines exist to automatically place special types of devices and there are other variations that
may be employed. However, the process is basically the same as above.
An interesting feature of process planning for electronic assembly is that the assembly operations for any
particular board are an ordered subset of operations taken from a technologically, strictly ordered set of
operations determined by the machines and processes available in the factory in which the board is being
made. T h e fact that these operations are strictly ordered prevents the type of combinatorial explosion of
possible operation sequences that can occur in other technologies.
As noted above, the assembly planning process is o n e of deciding which components will be inserted at
which step in the process or, equivalently, how they will be attached to the P/CB. U p to several hundred
components may be attached to a board and, in a typical factory, hundreds of different types of board are
produced each year.
Depending on t h e philosophy of inventory management as well as the degree of automation, production is
managed as a variation on o n e of the two basic approaches:
•
•
Batch Production
Flexible Line Production
4.2.1.1.1 Batch Production
Each work station or machine center on the production line is stocked specifically to meet the needs of a
particular board and a relatively large lot size of a particular board is run. Steps are normally taken to
balance t h e line to minimize idle time. When the lot is complete, the line is restocked and perhaps
reconfigured to produce a new board.
U n d e r batch production, a process plan is written for the particular board to be produced and the line is
stocked and configured according to this production plan.
In some factories, the factory floor is not configured as a production line. Rather, machines and workers
are functionally grouped and batches of boards move through the factory floor from work center to work
center in typical job-shop fashion. Materials are commonly issued in kits.
52
Computer-Aided Process Planning (CAPP)
4.2.1.1.2 Flexible Line Production
Taking into account the production schedule for some period of days or weeks into the future, all
components needed for assembly of the scheduled boards are assigned to particular work stations. As the
boards move through the line, they are automatically identified at each work station and the appropriate
component attachments are completed. Each work center can be viewed as a flexible machine center
(FMC) and nearly all the design and scheduling concepts applicable to F M C s can be applied. Lot sizes of
o n e may b e accommodated and just-in-time concepts applied. Balancing the line becomes a very difficult
task, but substantial a m o u n t s of idle time can be tolerated and justified on the basis of reduced setup time,
inventory reduction, improved yields, and the other benefits of this type of manufacturing philosophy.
This type of system is relatively intolerant of large a m o u n t s of component insertion by humans, because
the work task can change from m o m e n t to moment. Communicating o p e r a t o r instructions and monitoring
the operator's actions can be difficult. C R T monitors which present the o p e r a t o r instructions are used to
reduce the confusion, as are a variety of other machines which mechanically identify, for the h u m a n
operator, the c o m p o n e n t to b e inserted and its location o n the board.
Under the flexible line production philosophy, a process plan must also exist for each board to be
produced. However, t h e plan moves with the board, being accessed, say, by barcode, at each work station.
Moreover, the configuration and stocking of the line must attempt to take into account the requirements
of the collective process plans of all boards to be produced during the planning period. Ideally, o n e would
have all of these process plans available in advance in order to attempt to optimize the location of
components in relation to machine center capacity. However, such is rarely the case, and day-to-day
modifications are made.
4.2.2 The P l a n n i n g T a s k
In order to fully appreciate t h e planning task, it is helpful to understand how circuit boards are typically
designed.
4.2.2.1 Circuit Board Design
Computer-aided circuit board design was o n e of the first and most successful applications of C A D .
N o r t h e r n Telecom uses the Circuit Board Design System (CBDS) which was developed and is maintained
by Bell N o r t h e r n Research and is marketed by IBM. T h e r e are a number of competing systems, but all the
principal C A D systems for circuit board designs provide the designer with a highly automated environment
for conceptualizing and analyzing the functional properties of the circuit, choosing actual components for
implementing the circuit, and laying out the board. In addition, these systems produce a B O M and other
files that are used by purchasing and manufacturing for planning, machine programming, and other
activities. Figure 22 illustrates the relationship of process planning to C A D , C A E , and other elements of
a CIM architecture for the production of electronic systems.
F r o m a manufacturing standpoint, there are two data sets operating the C A D background which are of
particular interest. O n e is the c o m p o n e n t database from which either the designer or the C A D system,
itself, automatically selects the actual component to be used o n the board. This database may identify
preferred components from a purchasing, electronic, and manufacturing standpoint. However, the designer
may choose any c o m p o n e n t in t h e database, as required, to meet the design objectives and, while corporate
approval may b e required, may add new components to this database. Because of the rapid changes in
electronic technology and the need to remain competitive, the c o m p o n e n t database is constantly being
changed.
The other data set is in the form of sets of rules that either control or influence the selection of
53
Computer-Aided Process Planning (CAPP)
NEW PRODUCT
REQUIREMENTS
DESIGN
ENGINEERING (CAE)
NEW PRODUCT
REQUIREMENTS
Electrical
Silicon
Mechanical
Software
Documentation
Simulation
Standard Cells
Finite Element
Solids Modeling
DATA STORAGE &
ADMINISTRATION
MANUFACTURING
ENGINEERING (CANENG)
Product Line Up
Project Support
Networks
Test Programs
Costing
Post Processing
Process Dev. & Planning
PRODUCTION
Part Assembly
System Assembly
Functional Test
Packaging
Change Management
Design Transfer
Archive/Retrieve
»DUCTION CONTROL
PROC
PRODUCTION PLANNING
Schedules
Capacity Planning
Resources
Material
Detail Schedules
Customer Configuration
Τ
Τ
SHIPMENTS
FORECASTS/ORDERS
STS/i
Figure 22: A CIM Architecture for the Production of Electronic Systems
components and the manner in which they are placed on the board. These rules have two modes of
application. In the first mode, they are automatically applied by the C A D system to place components and
route the electrical paths on the board. In the second mode, these rules act as an advisor to the designer.
If a rule is violated, the designer is issued a warning.
Rules concerning manufacturing feasibility or desirability are normally included to o n e extent or the other
in the rule base for board design. For example, most systems will include rules for the placement of
manufacturing fixture locating holes on the board. By counting the numbers of and weighting the types of
violations, designs can be scored from the standpoint of ease of manufacturing. While the usefulness of
these scoring techniques is debatable, it illustrates the manner in which manufacturing concerns can be
handled at the design level. Accordingly, the design of circuit boards is performed in an environment that,
in theory, can b e very supportive of the application of criteria to simplify and reduce the cost of
manufacturing.
4.2.2.2 Planning Constraints
T h e planning task would be relatively straightforward if there were a unique and stable relationship
between a component to be attached and a method of attachment, and if the design of the board was in
consonance with preferred manufacturing principles. Indeed, o n e could simply assign an operation code to
all the c o m p o n e n t s in one's component database. Then, given a B O M , assign an operation to each
component, thereby specifying which components should be available at each work station. However, the
realities of circuit board assembly include the following:
54
Computer-Aided Process P l a n n i n g (CAPP)
(1)
Insertion feasibility is dependent on the specific configuration of the board; e.g., a D I P component
which can be auto-inserted by a D I P machine on o n e board cannot b e inserted on another board,
because there is insufficient clearance for the insertion tool.
(2)
Insertion feasibility and attractiveness is dependent on the specific machine and tooling. This is a
problem when o n e or m o r e design groups are producing designs for boards that may be produced
at several different facilities, each with different process capabilities.
(3)
T h e c o m p o n e n t is unavailable at the preferred insertion work station. Auto-insertion machine,
manual, and robotic work stations can only accommodate a limited variety of inventory. While
this problem can be overcome with sophisticated, material delivery systems, it will be m o r e
economical for many factories to simply pre-stock each work station. Accordingly, a component
that could be auto-inserted may end up being inserted by hand due to the physical limitation on
the inventory that can be accommodated at the auto-insertion work station.
(4)
D u e to machine breakdowns, the preferred or normal insertion method is unavailable. If a
machine is to be down for any significant period of time, the parts assigned to that machine must
b e affixed elsewhere and this implies a change in operator and machine instruction sets. If
feasible, an alternative to this is to reschedule production, although dynamic production
scheduling can b e complex and m o r e trouble than it is worth. In any event, o n e needs to
minimize t h e time needed to respond to unforeseen problems on the line, and this response will
most typically be a change in process plan.
4.2.2.3 Shop Aids
T h e overall planning process involves the development of the shop aids necessary to support these
operations. Shop aids include the instruction sets that drive automatic machines, test programs for
operating automatic test equipment, and operator instructions that must be issued to the floor in order to
execute the assembly of the board. In general, these may be grouped into two broad categories: (1)
assembly instructions for h u m a n operators and (2) the instruction sets, in the form of punched tape or
computer files, to o p e r a t e automatic equipment and to guide the process controllers that initiate and
terminate automatic machine operation, identify products, and control material transfer devices. Most of
these shop aids require a precise knowledge of c o m p o n e n t location and board geometry. This information
is provided by the C A D system.
However, a first-cut at assigning components to operations can be accomplished without regard to part or
board geometry. U n d e r ideal design conditions, the insertion methods normally associated with the
components would all b e feasible and preferable. This preliminary assignment of components to
operations can produce a tentative list of the operations that will produce the board and a list of parts by
each operation. These latter lists, coupled with component location and board geometry are what is
needed by the persons and computer programs which produce the shop aids.
Computer postprocessors which produce the instruction set for the operation of auto-insertion equipment
are of particular interest. T h e reason for this is that, while the feasibility of part insertion due to specific
board geometries can be addressed at a preliminary planning level, it must be addressed at the
postprocessor level. It is simpler to let the C A P P initially deliver a candidate list of parts for insertion to
the postprocessor, and let the postprocessor determine what it can insert while it is determining how to
sequence t h e insertions. If a part cannot be auto-inserted because of the specific joint configuration of the
component, board or tooling, the part is returned to C A P P for reassignment to another operation. T h e
order of choices is normally, first, auto-insertion, second, robotic, and lastly, manual. This process is
shown in Figure 23 and implies that the postprocessor must be able to identify insertion feasibility as well
as develop the sequence of c o m p o n e n t insertions and the path of the insertion tool. This does not
significantly complicate the algorithms used by the postprocessor.
55
Computer-Aided Process Planning (CAPP)
Other Shop
Aids
Component
by
Operation
Machine
•Instruction
File
Figure 23: The CAPP-Postprocessor Relationship
Accordingly, CAPP is responsible for producing an initial process plan and for dealing with those initial
proposals which were identified as infeasible or unattractive actions by the postprocessors.
4.2.3 P a r t s Numbering and Coding
T h e introduction of a new parts numbering or coding system is normally an expensive and time-consuming
task, whose cost is commonly very much underestimated. Accordingly, it should be approached cautiously.
C A P P systems seem to imply the need for a part numbering or classification system which provides a oneto-one link between a part and its assembly method. In turn, this means that each new component that is
added to the component database must be coded or otherwise linked to an assembly method.
Maintenance of such a system is expensive if the component database is constantly changing, and
potentially confusing if different manufacturing facilities view the assembly of the c o m p o n e n t in different
ways.
At Northern Telecom, the C A D file produces a parts list for the board. It contains a descriptive
engineering code, a nondescriptive specific part number, and a consistent, short English language
description of each part. There is enough information contained in the engineering code and the English
phrase to infer a great deal about the way in which each component can be attached. This happens even
though neither the engineering code nor the English description of the part were originally designed to
designate an assembly method. That is, it is possible to infer an assembly method from existing part
descriptions, and it is not necessary to create and maintain a new coding system. This is accomplished by
parsing the engineering code and the English phrase for key words and groups of characters in the context
of the board that is under consideration.
Alternatively, the parsing routing could b e used to automatically create an assembly code file by
component. This has not been necessary and would produce n o benefits from the standpoint of the CAPP
system.
56
Computer-Aided Process Planning (CAPP)
4.2.4 CAPP Aids CAD
T h e process plan that is produced at Northern Telecom lists the operations that are involved in the
production of a board and shows an estimate of the direct labor and/or process time associated with each
of these operations. W e are currently interested in assessing the degree to which making this cost
information available to the designer will influence the degree to which manufacturing cost and yield are
considered by t h e designer. This design aid could only work with a generative C A P P .
4.2.5 P/CB Production
•
A C A P P system reduces the labor cost of preparing a process plan. By itself, this is probably
not a strong argument for C A P P in electronic assembly planning. T h e a m o u n t of time spent
o n process planning, particularly initial process planning, is relatively low in comparison to
other technologies.
•
A C A P P system reduces the training costs of new process planners and mitigates the impact of
losing key personnel. It is not clear that a generative C A P P system for electronic assembly
can serve as an effective training aid for new process planners. A variant system is better at
this. C A P P may be useful when it comes to acquainting new designers of electronic boards
with manufacturing issues. By pointing out costs, the C A P P system might well be an effective
device for increasing designer sensitivity to these issues.
•
A C A P P system improves the consistency with which plans are produced. While this is true,
the issue of consistency is not of as much concern as in other technologies. In part, the
reason for this is that there are not the processing options available in electronic assembly
that exist in metalworking. However, the process of structuring C A P P uncovers
misconceptions regarding assembly feasibility. These misconceptions are uncovered as o n e
assembles the knowledge-base and rules for its application. T h e elimination of these
misconceptions will improve productivity. T o some extent, this is the result of pursuing a
generative rather than variant strategy.
•
A C A P P system provides the response time necessary to run a highly a u t o m a t e d CIM system.
As electronic assembly moves toward fewer manual insertions, the ability to rapidly change the
process plan for a board under a flexible machine center philosophy becomes increasingly
important. U n d e r a CIM architecture, there are compelling arguments for a generative CAPP
system, which can o p e r a t e quickly and with as little human intervention as possible.
•
A C A P P system provides a useful tool to improve the manufacturability of circuit board
designs. T h e extent to which this is true depends on the organizational and product
development philosophies of the firm. In firms which already assign a high priority to ease of
manufacturing, attaching the C A P P to the C A D system may not be useful. F o r others, it may
b e useful to provide the designer with a C A P P system which gives the designer immediate
access to an estimated conversion cost and explains the reason for the conversion cost by
showing the cost implications of the design on an operation-by-operation basis.
C A P P should b e designed to allow the process planner maximum control over its operation, and
alternatives should b e thoroughly explored before introducing new parts coding or classification schemes.
They may not be necessary.
57
Computer-Aided Process Planning (CAPP)
4 3 The Route Generator
In 1986, D E C was faced with how to integrate M R P II shop floor control, automated material handling,
factory data collection at the shop/center hierarchical level, and several cells at the cell/line hierarchical
level. With s o m e of these systems having already been implemented, and several others on the drawing
board, each system was designed independently of the other. Consequently, each system would have
addressed its routing and process data needs independently. If this had been allowed to continue, each
system would have had to be implemented alone, in the sense of manually maintaining its own private
copy of the r o u t e and process data.
T h e problem with standalone implementations that require much of the same data in c o m m o n is version
control. R o u t e maintenance and version control arises when route-sensitive systems are implemented in
t h e same environment but are not designed for integration. For example, when there is a need to update
t h e r o u t e because of an engineering change order, to change the standard route because of a sudden
downward shift in quality levels, or to modify the process to take advantage of new technology/ideas,
making a change to the manufacturing process can easily spill over into requiring modifications to process
definitions on other systems. Thus, redundant, manually maintained route data is undesirable.
4.3.1 T h e G e n e r a t o r
T o resolve this problem, instead of requiring multiple, redundant data maintenance activities to be made
on each system, the R o u t e G e n e r a t o r ( R G ) was developed as a single point of definition and control for
the generation and revision management of routes and related process planning data for all route-sensitive
systems.
O n e temptation to overcome was to try to build upon the existing process definition data structures within
the M R P II system. However, it was soon realized that the M R P architecture was incompatible, that it did
not support hierarchical routings, and that, as a business system, it did not support process engineering
activities; e.g., it assumes a straight line route flow. In most process flow charts, there are several branch
points that a process can take dependent upon any number of constraints.
T h e R G is an interactive, graphical, video terminal-based work flow generator application compliant with
the architecture previously described. It is used to converge the routing needs of each of these systems
into lone logical master route. O n c e defined, routing data is derived from this master route for any
system. Because there is o n e point of control for routing data, the integrity of routes between systems
should b e insured. T h e benefit of the R G is its ability to capture and communicate the various route
requirements for each of the factory control systems. Each process control system accesses its route data
by making B O P data management interface calls. Because this data comes from the same source, routing
data is consistent across all systems and is at the proper revision level.
Multiple revisions of a r o u t e (process) can co-exist for the same part number at the same time in the
manufacturing site. Additionally, the preferred process to be used to build and test a part can change
from time to time. Therefore, the R G allows for revision control of both part and process. This allows
factory systems to phase-in new processes and parts without losing visibility into the requirements for a
specific instance of a part and process. Systems that use the R G are truly integrated and have a common
reference system ( B O P ) that can be used to manage any number of system views from same route
definition.
4.3.2 Controller Views
T h r e e process control systems, each of which require a route, are referred to as controllers because of their
ability to control s o m e aspect of the manufacturing system. Each of these systems potentially requires
58
Computer-Aided Process Planning (CAPP)
more detail about the r o u t e flow, and each has different views and data needs of the same route. They
are:
•
Manufacturing Resource Planning ( M R P II)
•
W o r k Flow Control ( W F C ) and Material Handling
•
Factory Data Collection ( F D C )
4.3.2.1 Manufacturing Resource Planning
M R P II requires the most abstract view of the route. M R P IPs view is not for real time control purposes
and, therefore, does not require extensive route control data. Instead, M R P II is interested in financial
and capacity planning data related to the route. T h e data required is used by M R P II for capacity
determination and costing.
4.3.2.2 W o r k Flow Controller
The W F C takes a material handling point of view, based on a "material drop-off perspective. A W F C
needs route data so that it can match route setup requirements to current resource capabilities and
machine setup states to achieve optimal work flow.
4.3.2.3 Factory Data Collection
F D C potentially requires the most detailed route flow view. T h e F D C route flow view can include
standard operations, alternate operations, and various alternate rework operations irrespective of the way
an associated material handling system may be configured. Alternate rework operations may be
determined by the degree of seriousness of a failure o r some o t h e r significant set of parameters that are
used to determine what operation is to be performed.
4.3.3 Combined R o u t e Flow
T h e R G permits the creation of a single, user-defined logical route, providing multiple views for factory
systems in need of r o u t e flow data, yet maintains the continuity of o n e logical route.
Below is an example of how multiple r o u t e views can be derived from o n e logical r o u t e flow. T h e example
begins by listing a product r o u t e flow, without giving consideration as to how the process steps in the
route are eventually executed by the various process control system controllers. T h e example route flow
shown in Figure 24 is based strictly on the product requirements and the logical activities required to build
and test the product.
T h e sample r o u t e list is then translated into a logical process flow, as shown in Figure 25. It is at this
time that the engineer would define the route flow in a way as depicted in Figure 25.
T h e master r o u t e flow is then analyzed with respect to the needs of each route-sensitive system. In effect,
t h e generator for each controller selects certain process steps and ignores others, creating different views
of the same master route.
59
Computer-Aided Process Planning (CAPP)
4.3.3.1 M R P II View of the Master R o u t e
T h e Process Steps required for M R P are depicted in Figure 26. The normal cycle time for the initial
assembly process is short enough to not warrant detailed tracking by M R P II. H e n c e only steps 1, 5, 6, 9
and 12 are "seen" by M R P .
T h e M R P II view is:
•
•
•
•
•
Process
Process
Process
Process
Process
Step
Step
Step
Step
Step
1: Assembly Step 1
5: Assembly Step 5
6: Test Step 1
9: Test Step 2
12: Final Touch-up
Process
Step
1
2
3
4
5
6
7
8
9
10
11
12
Description
Assembly Step 1
Assembly Step 2
Assembly Step 3
Assembly Step 4
Assembly Step 5
Test Step 1
Rework Test Step 1
Retest Step 1
Test Step 2
Rework Test Step 2
Retest Step 2
Final Touchup
Figure 24: Sample Product R o u t e List
pass
pass
Figure 25: Master R o u t e Flow
60
Computer-Aided Process Planning (CAPP)
1
>-5->6
pass
>9
>M2
Figure 26: M R P View of the Master R o u t e
T h e activities that M R P II does not see are Process Steps 2, 3, 4, 7, 8, 10 and 11.
4.3.3.2 W F C View of the Master R o u t e
T h e W F C view is a different subset of the master route. The W F C view is affected by the physical layout
of the factory floor and t h e material drop-off points at each of the work stations. Assuming that Assembly
Step 4 and Assembly Step 5 share the same physical material drop-off point, the W F C view requires
Assembly Steps 1 through 4 but not Assembly Step 5 (see Figure 27). T o the W F C , the next standard
operation after Assembly Step 4 is Test Step 1 (Process Step 6).
1
>2
>3->>4—
pass
^ 6
>M2
Figure 27: W F C View of the Master R o u t e
T h e W F C view is:
•
•
•
•
•
•
•
Process
Process
Process
Process
Process
Process
Process
Step
Step
Step
Step
Step
Step
Step
1: Assembly Step 1
2: Assembly Step 2
3: Assembly Step 3
4: Assembly Step 4
6: Test Step 1
9: Test Step 2
12: Final Touch-up
N o t e in this W F C example that Rework and Retest are performed internally to each test step so that the
W F C never needs to know about Rework and Retest operations. Of course, if the W F C did need to know
about rework loops, then Rework and Retest Steps could be identified as part of its view.
4.3.3.3 F D C View of the Master R o u t e
FDC's view is yet another, m o r e detailed view of the route master flow. F D C needs to view any physical
drop-off steps required by a W F C , as well as Rework and Retest Steps. N o t e , however, that the F D C view
does not include Assembly Steps 2 and 3 (see Figure 28). The assumption is that F D C is not involved in
these two assembly steps, but a W F C must still deliver the product to these steps.
61
Computer-Aided Process Planning (CAPP)
F D C s view requires all the Process Steps except Steps 2 and 3:
•
•
•
•
•
•
•
•
•
•
Process
Process
Process
Process
Process
Process
Process
Process
Process
Process
Step
Step
Step
Step
Step
Step
Step
Step
Step
Step
1: Assembly Step 1
4: Assembly Step 4
5: Assembly Step 5
6: Test Step 1
7: Rework Test Step 1
8: Retest Step 1
9: Test Step 2
10: Rework Test Step 2
11: Retest Step 2
12: Final Touch-up
N o t e that F D C needs to know that the Rework Step is not the standard Process Step but, rather, is an
allowed alternative only if a failure path is required at the completion of either test step.
T h e R G is table driven such that an engineer wishing to expand the number of system views simply
registers the new view name in a master table along with a pointer that maps to the view-specific
subroutine that addresses the data requirements of that system view. Later, when that view is indicated to
the R G , the customized view-specific subroutine is executed, prompting the user for the view-specific data.
Still later, once the route definition has been approved and released, the process controllers make the
appropriate B O P data management interface calls referencing the same view name as originally input by
the engineer.
pass
pass
Figure 28: F D C View of the R o u t e Master R o w
T h e B O P data management interface calls are very powerful. Generally, controllers have two modes in
which they operate. O n e mode is to pass the status outcome of a previous step and allow the BOP
evaluation routines to evaluate the proper next step based upon the view being requested. Referring to
Figure 28, in a simple case where Step 6 results in a failure, then the logical next Step is a rework step,
Step 7. W h e n F D C requests the next step following Step 6 and supplies a "fail" status, the BOP evaluates
this request and returns the rework step, Step 7. If, however, the next step request was made by WFC, the
rework Step 7 is not seen and the correct response returned is Step 9. This is because it was determined
that the W F C view would not have to be concerned with whether or not a failure was detected at Step 6.
T h e o t h e r m o d e is for the controller to request all of the next steps for a given step that meet the view
specified. In this mode, the controller must be able to evaluate the alternate next steps and make the
decision on its own as to which step will be selected.
62
Computer-Aided Process Planning (CAPP)
4.3.4 Process M a s t e r
While the R G supports the traditional file structure of separate routes for each product, it additionally
offers a G T capability by combining the otherwise separate routes into o n e superset route. This master
r o u t e superset, called the Process Master (PM), is defined as a generic route flow template containing any
number of Process Steps (PSs) which can be applied to define the r o u t e of a family of similar parts or
products.
T h e P M is well suited to support manufacturing operations of closely related product lines. In fact, the
closer t h e alignment of process similarities within the PM, the m o r e efficient the P M becomes. For
example, a D E C video terminal model number VT240 is a m o n o c h r o m e terminal. A VT241 is identical to
the VT240, but has color capability added. T h e VT240 and VT241 terminals would be considered
excellent candidates for inclusion in the same family to share a single P M because of their similar route
flows.
A P M can have an unlimited number of PSs to support the members in the family of parts, but the most
efficient use of the P M occurs with the highest percentage of like PSs. As a point of comparison, the
VT100 terminal deviates significantly from the VT240 series and would be considered less likely to
effectively share the same P M .
Since the VT100 has fewer PSs in common with the VT240-241 process master, combining these two
dissimilar processes into o n e process master would not be desirable. T h e r e are tremendous advantages
that can b e derived from combining similar processes into o n e process master, such as a reduction in data
maintenance and redundancy, and the ability to apply an integrated G T approach to manufacturing process
families.
4.3.4.1 R o u t e View of the P M
Using the previous example of the P M family, the VT240 and VT241 would each require a R o u t e View
( R V ) of the PM. Both of the R V s would be mapped to the same PM. Almost all of the PSs would be
mapped for each R V due to the similarities between the build processes. Consequently, two part process
views have roughly 80 percent of the process steps in common.
However, if the VT100 were added as a member to the same PM family, not only would fewer of the
existing PSs b e usable by the VT100 route, but additional non-sharable steps would need to be added. It
would simply b e m o r e efficient to create a separate P M for a family of VTlOOs, rather than minimize the
utility of the existing family.
4.3.4.2 Conceptual A p p r o a c h
T h e R G uses t h e P M to define a superset of valid sequential activities for use as a template for each of
the individual parts within the P M flow. This P M template consists of the following components:
•
•
•
PM Header
Process Steps
Controller View
The components of the P M must be created in the order listed above. T h e P M H e a d e r data is created
first and identifies the historical information about its creation. T h e PSs then define the superset route
flow for a specific PM. T h e controller view points to the specific process steps that are viewed by each
controller.
63
Computer-Aided Process Planning (CAPP)
T h e R V points or "maps" to a subset of the PM by selecting the appropriate PSs from the PM template.
T h e R V consists of:
•
•
•
Part Master
R o u t e View Header
Controller Specific
T h e R V Header is attached to the PSs of the same PM. T h e R V inherits all data associated with each PS,
as well as any controller views associated to those PSs. Controller specific data is attached to the R V
Header.
4.3.4.3 T h e P M and the R V
The relationship of the two data structures, the PM and the R V , is depicted in Figure 29.
PROCESS
MASTER
PART PROCESS
VIEW
Process
Master Header
Part
Master
y
y
Route View Header
Process Steps «<•
y
y
Controller
Specific Views
Controller
Views
Figure 29: Data Relationship Between the Process Master and the R o u t e View
64
Computer-Aided Process Planning (CAPP)
5. Planning Facilities
5.1 The Process Industry Solution Center
Time is the essence of manufacturing competitiveness. For this reason, the focus of t h e Process Industry
Solution Center, a joint partnership between Hewlett-Packard and Fisher Controls, is enterprise-wide
information integration; from product development through production, distribution, marketing, and sales.
T h e Process Industry Solution Center is a meeting and demonstration facility developed around the
operations of a simulated chemicals manufacturer. T h e Process Industry Solution Center debuted in 1988
as the C I M Technology Center.
T h e Goal of the Process Industry Solution Center is to illustrate to customers as well as help them:
•
Balance costs, quality, features and availability
•
Shorten development, manufacturing and delivery cycles
The Process Industry Solution Center believes C o m p u t e r Integrated Manufacturing (CIM) must build on
the manufacturing management foundation already established within an organization. T h e basic strategy
of the Process Industry Solution Center is to, as painlessly as possible, migrate to an open, standards-based
integrated environment by building on and adding to existing applications.
Because no two process manufacturers are alike, the Center doesn't p r o m o t e "one-size-fits-all" solutions.
Its approach is to analyze operations and information flows, identify strategic opportunities for
improvement, and quantify the benefits these opportunities offer.
5.1.1 The M a r k e t
Each of t h e industries addressed by the Solution Center rely on a combination of batch-oriented processes
and discrete manufacturing techniques. Market conditions are forcing these sectors to examine CIM as a
business solution. F o r instance, the rate of new drug introductions in pharmaceuticals requires producers
to become m o r e flexible, while tightening F D A and E P A regulations, and consumer expectations, are
pressing them to improve quality.
These demands are boosting the market for CIM. According to Frost & Sullivan, the market for
integrated batch process control systems serving these sectors will exceed $1 billion by 1994, a 100 percent
increase over five years. Over half of the growth will come from foods, fine chemicals, and
pharmaceuticals.
5.1.2 T h e Solution C e n t e r Demo
T h e first part of the presentation focuses in the importance of time-based competitiveness: the ability to
get product to market sooner. T h e next part homes in on modeling both the business and manufacturing
process, with the goal of simplification. Various scenarios and control methodologies are explored,
informed by the collective experience of the Solution Center's staff in process applications and CIM.
T h e final part of the program focuses on implementation. H e r e , a 30-minute comprehensive
65
Computer-Aided Process P l a n n i n g (CAPP)
demonstration shows how a batch-oriented process m a n u f a c t u r e r - t h e Mighty Fine Chemical Co., a
producer of specialty chemicals-would use integrated O p e n Systems to cut product lead times.
As the d e m o begins, the Mighty Fine plant is already running with a predetermined master schedule and a
short-term production schedule, extending four or five days. T h e process itself mixes and reacts up to four
ingredients into four different end-products, simulating the type of flexibility characteristic of today's
specialty chemical producers.
In t h e d e m o , the M R P II system ( C I M P R O , from Datalogix International) has already downloaded the
current work order backlog for the week, which the finite scheduling system (Schedulex from Numetrix,
Ltd.) converts into round-the-clock daily schedules. Those schedules are then downloaded to the
supervisory control system. A choice of the following supervisory systems are featured:
•
Monitrol from Hilco Technologies
•
PMIS from Bradley-Ward
•
CIM 21 from Industrial Systems Inc.
Within the plant, the supervisory system sends orders to the Fisher P R O V O X p l u s plant floor distributed
control system (DCS) to make various batches, o n e at a time. T h e D C S in turn is linked to a Fisher
Controls U N I V O X line operator station.
O n c e the D C S reports that the batch has been made, the supervisory system schedules a quality control
test from the plant production laboratory by notifying the laboratory information management system
(LIMS), based on HP's L a b / U X software. T h e plant is also equipped with a maintenance management
system (MCS-II from Diagonal Data) that schedules and tracks routine and emergency repairs. Provision
is made for the operation of a PLC-controlled line for packaging the finished chemicals into drums.
T o demonstrate the flexibility of the system, a breakdown is staged on the production line. T h e main
reactor, a 2,000-gallon tank, suddenly malfunctions, requiring a rerouting of production to a larger, less
efficient 3,000-gallon tank; the issuance of a repair work order; the scheduling of extra production lab tests
to determine the quality of the batches produced both before and after the breakdown; and the adjustment
of plant schedules to account for the less efficient production capability.
T h e adjustments start with notification by the D C S to the supervisory system. This in turn prompts the
issuance of repair work orders from the MCS-II maintenance management system, extra quality tests from
the H P L a b / U X LIMS system, and a rerunning of production schedules on the finite scheduler.
5.1.3 New Tactical Demo Added
T h e Tenafly center has long provided an executive-level system demonstration aimed at corporate
management and M I S staff. It has now added a hands-on tactical version for technical users, such as plant
engineers, to actually operate all systems except for the M R P master scheduling.
F o r instance, in the H P L a b / U X LIMS system, the o p e r a t o r can override the system and perform historical
trending o r sample tracking, adjust automatic specification testing procedures, or change automatic test
schedules for out-of-spec samples. In the DCS, he or she can change both the formulations, process trains
(routings), and the operating parameters of the reactor tanks.
T h e computer systems are all H P 9000 workstations running H P / U X . They are networked via TCP/IP
Ethernet. Applications are integrated using the Network File System (NFS) and H P Sockets, an
applications and communications interface. T h e supervisory and plant management functions are managed
66
Computer-Aided Process Planning (CAPP)
by the H P computers. They link to the Fisher control environment via Fisher's C H I P / U X (Computer
Highway Interface Program/Unix).
T h e changes to the Solution Center's p r o g r a m s - f r o m awareness to service and i m p l e m e n t a t i o n - a r e the
result of customer input. For instance, though both H P and Control Associates will provide
implementation and strategic consulting services, the Center will also work with third-party service
partners designated by the customer.
T h e demos at the Process Industry Solution Center will continue to evolve. According to process industry
consultant Henry F a s t e n of H P , who organized much of the computer hardware and software portion of
the demo, additional applications are being added, including M A N B A S E from M A I Manufacturing
Systems Inc. T h e d e m o will in many cases offer choices of multiple packages for any given application,
such as the three already offered-Monitrol, PMIS and CIM 2 1 - a t the supervisory level.
Currently three days a month are reserved for visits by area companies to the Solution Center. A short
list of previous visitors include American Cyanamid, Ciba Geigy, Hoescht Celanese, Hoffman LaRoche,
Lederle Labs, Lever Brothers, and U n i o n Camp. An estimated $7 million in sales were attributed to the
CIM Technology Center between 1988 and 1991, a level of success that will continue at its successor, the
Process Industry Solution Center.
5.1.4 Conclusion
Endeavors such as the P.I. Solution Center provide users, and vendors an opportunity to view an
operational system-even if only hypothetical. This opportunity fosters further development and activity in
CIM. This will, o n e hopes, provide for m o r e efficient manufacturing processes.
5.2 Honeywell's Integrated Manufacturing Facility
Many manufacturers have already studied the feasibility of integrating building control with manufacturing
control in a single, integrated system, in an effort to increase manufacturing competitiveness.
Building-control functions usually include monitoring and controlling environmental applications in a
facility, such as heating/ventilating/air conditioning ( H V A C ) , humidity, air pressure, lighting, fire alarm
systems, utilities systems, plant security systems, safety interlocks, and energy management and
conservation.
Manufacturing control functions typically include monitoring and controlling such manufacturing
applications as data acquisition, regulatory control functions, discrete/logic functions, batch functions,
sequencing, event-initiated processing, analysis and report generation, historization, and interfacing to
plant-wide communications systems.
5.2.1 Sample Configuration, Typical Manufacturing Facility
T h e physical operations of typical manufacturing facilities usually include several areas, such as receiving,
manufacturing, packaging, storage, and shipping. O t h e r physical operations in an industrial facility may
include utilities (such as boilers, refrigeration units, and cogeneration units) and environmental process
units (such as wastewater system, thermal oxidizers, and scrubbers). O t h e r manufacturing occurs in
extremely sensitive, controlled environments, such as clean rooms and laboratories.
Figure 30 shows all physical operations within a typical manufacturing facility (manufacturing process
areas, utilities, and environmental process units).
67
Computer-Aided Process Planning (CAPP)
Manufacturing Facility
Laboratory
a
Receiving
Area
—•
Mfg.
Area
—•
—• Packaging
Area
Storage
and
Shipping
V
Clean
Room
Utilities:
• Boilers
• Refrigeration
Units
• Cogeneration
Units
Environmental
Process
Units:
• Wastewater
• Thermal
Oxidizers
• Scrubbers
Laboratories/
Cleanrooms
Figure 30: Physical Operations, Typical Manufacturing Facility
Historically, building-control and manufacturing-control networks were designed separately, with
overlapping capabilities. Since the two types of networks were seldom integrated, they almost always had:
•
•
•
•
Different system architectures
Incompatible hardware and software platforms
Inconsistent data bases
Lack of communication between manufacturing control and building control
R e d u n d a n t , costly, cumbersome communication networks still exist in many industrial facilities.
Figure 31 illustrates the traditional building control focus.
Leading manufacturers are now gaining a competitive advantage by analyzing the interrelationships of their
building control network, their manufacturing control network, and their business goals. The Honeywell
approach to creating an Integrated Manufacturing Facility provides manufacturers with two types of
plant-wide data communications:
•
Bidirectional horizontal communication-from the receiving dock to the shipping dock: this
type of communication links work areas and utilities with the entire manufacturing process
68
Computer-Aided Process Planning (CAPP)
Building
Control
Focus
Manufacturing Facility
Laboratory
Receiving
Area
—•
Mfg.
Area
·.
—»
Packaging
Area
—»
t
Storage
and
Shipping
Clean
Room
Utilities:
Environmental
Process
Units:
• Boilers
• Refrigeration
Units
• Cogeneration
Units
• Wastewater
• Thermal
Oxidizers
• Scrubbers
Security
Laboratories/
Cleanrooms
Figure 3 1 : Traditional Building Control Focus
•
Bidirectional vertical communication-from sensors to the boardroom: plant floor information
flows upward to the administrative/management network, and strategic/tactical information and
operating strategies flow down to the shop floor
Building and manufacturing information is made available to those who need it: operators, engineers,
maintenance and support personnel, and plant management.
These bidirectional horizontal and vertical communications capabilities are designed to help manufacturers
make m o r e informed, timely decisions concerning their operations.
5.2.2 Challenges Facing Today's Manufacturing Facilities
"Under-rooP industrial facilities that house all their manufacturing equipment in an enclosed environment
face many control challenges. These challenges result from the lack of integration with a building control
system and include:
•
•
•
Inconsistent product quality
Inflexible control and automation systems
Excessive downtime (often caused by a safety system fault)
69
Computer-Aided Process Planning (CAPP)
•
•
Inefficient analysis and reporting capabilities from using separate systems
Inconsistent measurement, control, and management of facilities costs-particularly utilities
These shortcomings can be addressed individually, as follows:
•
Inconsistent Product Q u a l i t y - I n d o o r humidity, temperature, air pressure, and air quality must
be measured and controlled. T h e internal building environment often has a direct impact on
product quality and plant profitability in many manufacturing processes.
•
Inflexible Control and Automation S y s t e m s - M a n y manufacturers are unable to quickly and
flexibly change the environmental conditions of their facility as quickly as they change recipes
for product manufacturing. This inflexibility can adversely affect the quality of fine chemical
products and o t h e r products that require close tolerances for temperature, humidity, and air
pressure parameters during their production.
•
Excessive D o w n t i m e - T h e inability to integrate a safety shutdown alarm with an intelligent,
staged shutdown of the process can cause excessive downtime and lost production time.
•
Separate Systems Performing Analysis and R e p o r t i n g - C o n v e n t i o n a l manufacturing facilities
usually have analysis and reporting capabilities spread throughout the plant in independent
systems. Multiple operating stations generate reports in different formats among various
manufacturing areas. This approach makes it difficult to collect, analyze, and historize
important events. In addition, operators must be trained to use a variety of systems, formats,
and protocols.
•
Inconsistent M e a s u r e m e n t , Control, and M a n a g e m e n t of Facilities C o s t s - C o s t s of utilities
and environmental units are difficult to measure and control. Many facilities previously had
n o way to track these costs or allocate them back to product lines, plant areas, or
departments. In addition, the production cycle and the physical facility may have peak energy
needs that occur simultaneously, resulting in "high peak" energy billing and/or "brown out"
conditions. Integrating the manufacturing process with utilities and environmental process
units can help manufacturers: predict when peak energy usage will occur; schedule and
allocate energy usage costs efficiently; and distribute utility resources (chilled water, steam,
compressed air).
5.2.3 The Integrated Manufacturing Facility Solution
Figure 32 illustrates an Integrated Manufacturing Facility Solution, as envisioned by Honeywell.
T h e integration of a building control network with a manufacturing control network can offer users these
competitive advantages:
•
Better Product Q u a l i t y - I n t e g r a t e d building and manufacturing control strategies help keep
the internal facility environment consistent with the product being manufactured, resulting in
products of consistent quality and m o r e productive workers
•
Flexible Manufacturing Capabilities-Integrating process control and building control allows
manufacturers to respond to changing market demands with quicker setups and faster
transitions between product runs
70
Computer-Aided Process Planning (CAPP)
Plant Management
Manufacturing Facility
Manufacturing
Control
Focus
Laboratory
Receiving
Area
JZJL
Mfg.
Area
*
Packaging
Area
Storage
and
Shipping
Process
Control
Clean
Room
Utilities:
Security
Environmental
Process
Units:
• Boilers
• Refrigeration
Units
• Cogeneration
Units
Γ
Building
Control Network
Material
Handling
• Wastewater
• Thermal
Oxidizers
• Scrubbers
Laboratories/
Cleanrooms
Packaging
Control
Manufacturing
Control Network
Figure 32: Integrated Manufacturing Facility
•
Increased Uptime, Reduced Product Costs, and Lower Scrap Rates--The Integrated
Manufacturing Facility can warn production operators when environmental conditions are out
of specification, or when a potential safety hazard exists before out-of-specification conditions
or hazards occur; early alarming gives operators time to react to this information and correct
it, before a manufacturing control problem occurs; if a shutdown situation should occur, early
n
n
alarming can help stage a soft shutdown and eliminate costly startups
•
Coordinated Supervisory and Reporting Capabilities-The Integrated Manufacturing Facility
integrates analysis of building control and manufacturing control, providing:
•
•
•
•
•
•
Improved ability to comply with F D A and E P A regulations
A convenient "single-window" for reporting and tracking
History and trending analysis for both systems
A consistent operator interface
Reduced operator training
Improved Management and Tracking of Facilities C o s t s - T h e Integrated Manufacturing
Facility can measure, control, and manage facilities costs, providing-plant operations personnel
with tighter tracking and billing of operational costs to appropriate manufacturing units, and
optimized energy conservation
5.2.4 Manufacturing Applications
Internal cultural and organizational issues can sometimes impede even the best integration efforts.
Fortunately, many industries are moving quickly toward focusing on both building control and
71
Computer-Aided Process Planning (CAPP)
manufacturing control. These manufacturers are looking beyond departmental barriers to create
integration solutions for a variety of applications-from simple, single-loop applications to those that are
extremely complex. Fast, fundamental benefits occur in industries that recognize the positive impact of
control integration on the quality of products being manufactured. For example:
•
P h a r m a c e u t i c a l s - h a v e stringent ambient temperature, humidity, and pressure requirements in
manufacturing, laboratory, and animal room environments. In addition, many F D A
requirements now extend beyond the process system to include building control. Integration
between building control and manufacturing control can help pharmaceuticals manufacturers
control these processes m o r e tightly, thereby improving product quality and meeting
increasingly strict federal regulatory requirements.
•
Food, Beverage a n d C o n s u m e r Goods-face increasingly complex formulations and processes.
A need exists in these industries for information to b e shared between facility services and the
process, so that a wider variety of products can be tightly controlled during the production
process. Integration provides better data-sharing and communications throughout the facility,
as well as consistently high-quality products.
•
Textile Fiber Industries and P a p e r Products C o n v e r s i o n - h a v e strict humidity and temperature
control requirements. Integration of building control with manufacturing control is crucial to
the consistent, cost-effective production of quality products.
•
Silicon Chip M a n u f a c t u r e r s - s i l i c o n chip manufacturers face sophisticated control needs
within clean room and assembly areas. In addition, the building control system often:
•
Annunciates alarms for toxic material detection and provides safety warning systems for
notification of occupants
•
Provides focused control solutions for many sensitive applications
•
Controls process waste
Integration of building control with manufacturing control in this type of application helps manufacturers
maintain quality and reduce scrap.
5.2.5 Approaches To Achieving An Integrated Manufacturing Facility
T h e r e are two basic approaches to achieving an Integrated Manufacturing Facility. In the first approach,
manufacturing process requirements drive the integration, and commercial building controllers are
integrated into a higher-level industrial control system.
In the second approach, building control system requirements drive the integration, and individual
industrial control devices are integrated into a building control system.
Manufacturing process requirements drive, e.g., photographic film manufacturing (see example below) and
parenteral pharmaceuticals manufacturing; building control requirements drive, e.g., laboratories and
cleanrooms.
By way of example, the following paragraphs describe the use and benefits of the Integrated Manufacturing
Facility in a photographic film production facility.
In many manufacturing processes, such as photographic films, the building environment is a process
parameter that directly impacts product quality and plant profitability. Examples of building environment
72
Computer-Aided Process Planning (CAPP)
process parameters include the measurement and control of humidity, temperature, pressure, and air
quality . As manufacturers a u t o m a t e their process control systems, they also study how to tightly integrate
their building control systems with their process. These building control systems typically control heating,
ventilating and air conditioning ( H V A C ) and are candidates for integration into a single system-again,
known as an Integrated Manufacturing Facility.
Because the building environment and process are highly interactive during photographic film production,
a film plant needs to be completely enclosed, or "under roof." T h e product, be it in the form of raw
material, in-process inventory, or finished goods, is sensitive to environmental conditions during both
storage and processing. Because of the length of time film spends in various phases of storage, the storage
environment is often critical to the quality of the final product. T h e processing phase is typically much
shorter in duration and therefore is less dependent on environmental conditions. However, this phase is
still important, because conversion takes place during processing.
5.2.6 Process Description
Time of exposure to conditions of temperature, humidity, and light during storage is a critical quality
parameter. Product-dependent variables during manufacturing include drying pressure, temperature,
humidity, and air quality. H o w these variables are controlled can make the difference between an
acceptable product and a rejected product.
The process flow in a film plant begins with raw material storage of chemical compounds, such as paper
and film backings, water solvents, resins, and active ingredients.
T h e initial processing stage is called solution manufacturing. Next comes a coating process. After the
coating phase, t h e film dries in a multi-zone continuous dryer. Pressure, temperature, and flow rate are
critical to maintaining product quality during this drying process. T h e final phase of photographic film
production is the converting and packaging process. Most of this process is performed in a "lights out"
environment because of film's inherent sensitivity to light.
Most film plants today have separate process control, building control, fire protection, and safety systems.
This control approach can result in duplication of monitoring and operating costs and/or poor or
nonexistent communications between systems.
Several problems in a photographic film plant present opportunities for using an Integrated Manufacturing
Facility. F o r example, pressure must be tightly controlled in the various storage and processing rooms, as
well as within some of the process units, such as continuous dryers. Product quality often depends on very
stable and consistent airflow patterns throughout the manufacturing process.
In addition, separate safety shutdown systems are difficult to monitor and diagnose. Unnecessary
shutdowns caused by faulty sensors or system errors usually take hours to investigate and recover from,
often causing hours of lost production and product waste. Connecting these critical personnel safety
systems into an integrated manufacturing facility system not only reduces waste and downtime but also
speeds diagnostic maintenance and system recovery efforts.
5.2.7 Solutions and Benefits
Plant personnel have repeatedly expressed a need for a system that provides alarms, history, trends, and
reports to: prevent upsets leading to quality defects; satisfy regulatory, customer, and management
requirements; and establish correlations between quality of products and environmental conditions.
A system of this type would provide operators with quality data that displays storage parameters as well as
73
Computer-Aided Process Planning (CAPP)
process parameters for any batch, lot, or roll.
Potential benefits of building and manufacturing integration in a photographic film plant include improved
quality-i.e., m o r e consistent production results from minimizing process variability-and waste reduction,
increased uptime, and reduced training, spares, and support costs for various separate systems-i.e., an
integrated system quickly identifies problems, establishes correlations, saves time, and eliminates
finger-pointing
between working groups or departments. This leads to m o r e productive use of personnel
in solving plant problems, lowering costs, and improving overall manufacturing competitiveness.
5.2.8 Conclusion
A n Integrated Industrial Facility can provide world class manufacturing benefits to manufacturers in a
variety of industries. Honeywell claims to be the first control supplier to bring this integration technology
to control customers on a worldwide basis.
Integration of manufacturing control and building control can help manufacturers achieve and maintain:
•
•
•
•
•
•
•
•
•
•
Consistent production of quality products
Flexible manufacturing capabilities
Increased u p t i m e
Reduced product costs
Lower scrap rates
Tight, trackable compliance with F D A and E P A regulations
Improved management and tracking of facilities costs
Integrated plant-wide communications
High levels of employee safety
Energy reduction programs
Honeywell believes it can help achieve and sustain the Manufacturing Competitiveness of its customers
through the Integrated Manufacturing Facility.
74
Computer-Aided Process Planning (CAPP)
Vendors
T h e following list of products was taken from a 1989 research report by the staff of United Technologies
Research Center, E. Hartford, CT. At that time there were 134 C A P P systems; however, the majority of
these systems were either research systems, in-house systems, or systems developed in academe. Often the
researchers failed to give full information regarding the systems developer or the systems, themselves. T h e
systems listed below are those that are complete (not partial, quasi-, or n o n - C A P P systems), commercially
available, and included sufficient information to be useful for manufacturing applications. Information on
all systems studied by the researchers may be obtained by contacting CAM-I Inc., 1250 E. Copeland Rd.,
Suite 500, Arlington, T X 76011; 817/860-1654; F A X 817/275-6450
System:
Vendor:
AC/PLAN
American Channels, Inc
Lexington, M A
•
System:
Vendor:
Alphagraphics
Birsch, Birn & Partners
Ft. Lauderdale, F L
•
System:
Vendor:
A variant, G T oriented system; primary focus on classification and coding.
Autoplan
Metcut Research Associates, Inc.
Cincinnati, O H
•
System:
Vendor:
A hybrid (variant/generative combination) system using graphics for interactive selection of
resources.
C A P P (CAM-I's A u t o m a t e d Process Planning)
Computer-Aided Manufacturing International
Arlington, T X
•
System:
Vendor:
O n e of t h e oldest and most commonly used variant process planning system; uses G T
methods.
CutPlan
Metcut Research Associates, Inc.
Cincinnati, O H
•
System:
Vendor:
A n enhanced variant planning system; uses keywords to pick o u t the most similar plan; uses
search function to choose operations from other plans.
GT-based, variant system.
CutTech
Metcut Research Associates, Inc.
Cincinnati, O H
75
Computer-Aided Process Planning (CAPP)
•
System:
Vendor:
Expert machining operation detailing program; selects tools, cutting parameters (selection,
speeds, feeds), tolerances, cost estimating.
GECAPP-PLUS
General Electric
Albany, N Y
•
System:
Vendor:
Hybrid modular system; modules may be purchased separately; limited generative capability.
IntelliCap
CimTelligence
Lexington, M A
•
System:
Vendor:
A variant system combining AI, G T , and relational database technologies.
IntelliGen
CimTelligence
Lexington, M A
•
System:
Vendor:
A n AI, GT-based shell system designed to capture user's expertise.
LOCAM
Logan Associates
Natick, M A
•
System:
Vendor:
A popular hybrid system; user logic stored using decision tables.
MultiCAPP
Organization for Industrial Research
Bedford, M A
•
Variant system similar to CAM-I CAPP; besides G T code, retrieves plans by matrix, variance
code matching (similar part families), and information within a plan.
76