Robotics & Computer-Integrated Manufacturing, Vol. 10, No. 1/2, pp. 65-70, 1993 0736-5845/93 $5.00 + 0.00 Printed in Great Britain ~31992 Pergamon Press Ltd

• Paper

COMPUTER-AIDED PROCESS PLANNING--STATE OF THE FUTURE DEVELOPMENT

W. EVERSHEIM a n d J. SCHNEEWIND

WZL--Lehrstuhl fiir Produktionssystematik, Aachen, Germany

ART AND

Computer-aided process planning (CAPP) is regarded as the critical link between design and manufacturing. Particularly in the integration of computer-aided manufacturing, process planning plays an outstanding role in the integrated flow of information.

This paper gives a broad view of today's situation in computer-aided process planning in a real industrial environment. Characteristics for the classification of CAPP systems are derived and the main trends in the future development of CAPP software are pointed out. Feature-based modelling of manufacturing processes as the basis for integration-oriented software development is briefly described.

1. I N T R O D U C T I O N Computer-aided process planning (CAPP) is regarded as playing a key role in the development of computer- integrated manufacturing (CIM) because it forms the link between design and manufacturing. In the past development of CA systems has mainly been concen- trated on CAD (computer-aided design), NC pro- gramming (numerical control) and other systems and so today CAPP in the context of an integrated infor- mation flow is regarded as the weak point. 1-3

The development of software supporting different process planning and NC functions typically did not consider the hierarchical structure of process plan- ning, operation planning and NC programming. 4 Efforts to integrate the independently developed sys- tems led to the following problems: 5-7

• use of CAD data is difficult because of different data structures,

• redundant data storage, • inconsistent databases, • insufficient representation of technological data

and • different feature understanding in CAD, CAPP

and NC programming.

In this paper the state of the art of CAPP systems in today's industrial environment will be described, par- ticularly stressing the logical sequence of functions for generating control data. It will not give a survey of CAPP systems, which Alting and Zhang and Ever- sheim and Schulz already have. 3,a Then, future trends in commercial CAPP systems are pointed out. Finally, a new approach to modelling manufacturing processes as a basis for CIM is briefly discussed. This approach

is supposed to be the basis for future software develop- ment in the field of CAPP.

65

2. STATE OF TH E ART IN C A P P The task of process planning usually covers a series of worksteps. As the link between design and manufac- turing its input is the product description and its output is production instructions. In between, various subfunctions have to be carried out taking into con- sideration different order or company-specific require- ments.

Based on the interpretation of the design data the input material and the process activities and their sequence are determined. Then the machine tool and fixture are selected and the times are calculated. The result is documented in the process plan. Concerning NC data generation, process planning only includes the decision whether to use a NC controlled machine tool or not. If using a NC controlled machine tool, it is necessary to detail the process plan by determining the operations and sequencing them (Fig. 1). In detail the so-called operation planning covers:

• definition of the workpiece geometry for NC ap- plication,

• decomposition of the process activity into opera- tions related to a single tool use,

• calculation of speeds, feeds and cutting depths and • selection of tools.

To generate the NC program further steps such as determination of tool path parameters and the tool position points and switch commands have to be executed to come to the CL-DATA (Cutter Location

66 Robotics & Computer-lntegrated Manufacturing • Volume 10, Numbers 1/2, 1993

&x~ ...................................... ",.N\\\\\\\\\\\\'~.; ....................................... ~.N~ ~ f ~ Process Plan ~x~, Process process I resource I I ~ 1 / Planning" I mat su re"120037

N wor ace ~ f ~ ~, Operation Plan

~ ~ / Operation"/ Operation tool ~ • roughturn. 471

P l a n n i n g finishing 382 ~ tool ~. .-, J| drilling 1 675

I ~P / ~ -~ NC-Program = NC- N G x z

tool path/switch rogramming N10 G91 command ~ , ~ N30N20 2000 900

Fig. 1. Scope of process planning.

DATA) file, the control neutral format of the NC program.

Computer-aided process planning is traditionally based on two approaches, the variant approach and the generative approach (Fig. 2). The variant ap- proach originated from the first attempts to use com- puter-aided support in the field of process planning which started with simple retrieval and text editing as part of MRP (Material Requirement Planning) systems. 9 Order independent standard process plans are stored in the process plan archive. A standard plan

similar to that to be generated is first retrieved by the help of classification and coding and then edited for the new part. In this case, computer support is restricted to assistance in manual process planning activities and so the quality of a process plan is still dependent on the knowledge and experience of the process planner.

Compared to manual process planning, the variant approach is advantageous in increasing the informa- tion management capabilities. Company-specific pro- cess planning knowledge can be structured and stored to standardize process planning procedures. This fin- ally leads to significant time reduction in this area especially for companies where products do not vary much. The main reason for the wide application of the variant approach probably is the fact that the invest- ment required is less and that the development and hardware costs are lower. 3

Systems based on the generative approach support the process planner with various functions or enable the fully automated processing of functions. The avail- able resources and the rules of manufacturing, in the form of decision logics, algorithms etc., are stored in the system and enable a consistent, reproducible plan- ning procedure, input such as the workpiece descrip- tion for example is given either interactively or via an interface from CAD. Much effort has been spent on interfacing CAD and CAPP, recently concentrating on the feature approach which will be discussed later in this paper.

The generative approach is complex and a genera- tive CAPP system is difficult to develop making great demands on the programming technique. Regarding the rapid development of AI, its use seems to be promising for this application. Some systems that cannot be classified as either based on the variant or the generative approach are called 'semi-generative'. 3

iii ̧i ̧i zi i̧ ii iil ¸i iii iiiiiiii!iiii o hiiiiiiiiiiiiiiiiiiii i̧iiiiil iiiiiiiiiiiiiiii iiiiiii iliiii!iiiiii ill !!!i!!ili i i fill i ii!il i lil ~, i ii!i!!i!ii:-iii i i!ili i iii!iiiiii! i i~!i=: i = . i~i~:~i~ ~; i~ ~::!::i i!=.!! = . ~;.!,~!:~ !~,,!:,! !~:!!~iz!~:: ~'.i!i~.~i i ili iii! i i i i!i!i!i=i i!i!iiii~i iiiili~.!iii!ii~! ~

Variant Aporoach --~--q~--~- ~- is similar Io C

Process Plan Cx

01 matenal supply 02 turning 03 grinding

Generative Approach

I I I 01 material supply I I 0 2 t u r n i n g

r l 03 g n n d i n g

',.&,cAI ('Al:pp: Artificial Intelligence ~ Computer Aided Process P lann ing . .~

Fig. 2. A p p r o a c h e s to C A P P .

~ / ~ / / , ' / / / / / / t . , , , . , , . . , , , , C haracte n stt cs.,.,,.,,,,,,

• comparable to manual procedure

• planning results depend on experience/ knowledge of a process planner

edevelopmenl (Software) and hardware costs are lower

• support for/automated proceeding of processing decisions

• consistent, reproducible process plan

• effective for small batch sizes

• long development, high investment

,, •prefered application for AI in CAPP

C AP P state of the art and future development • W. EVERSHEIM and J. SCHNEEWlND 67

Programming Technique]

- AI- Technique I - Decision Table I )

I - Variant Planning | - Generative Planning ) i~:!lC::,t a .

Process -

/-Turning E ~ - ' / " Milling L-on,,ioo ] 1

Hardware

] Wcrkstation

~,. Planning Tasks I " interface to CAD f Degree of Automation

L~ description language I - interactive I g " I automat I

L "autOmated ,~

Fig. 3. Characteristics of CAPP systems.

CAPP systems can be classified by various criteria which characterize the area of application (Fig. 3). Beside the planning approach, the workpiece spec- trum and the plannable processes define the field of application of a system. Depending on the workpiece spectrum, the required functionality of a system can vary. For process planning for sheet metal parts, for example, additional functions for nesting and bending are needed.

The available planning functions, the degree of automation and the way of describing the planning task are further characteristics that describe the func- tionality and point out the requirements for integra- tion with CAD. The range of existing solutions covers systems with interactive input without workpiece de- scription as well as those with a system-specific lan- guage for workpiece description and systems that work on the basis of CAD data.

Highly competitive personal computers (PCs) have been developed in recent years. Particularly for small and medium sized companies, CAPP systems on PCs are an efficient start to CAPP. Advantages are the good value of such systems, the independence from large, centralized hardware and the convenient ways of designing the user interface.l°' 1

Such a CAPP system for a PC was developed at WZL--Laboratory for Machine Tools and Produc- tion Engineering in cooperation with six medium- sized enterprises. The system contains modules for the generation of process plans, data handling and admin- istration of planning results (Fig. 4). For all functions the process planner is supported by resource data from a relational database. An interface to PSC (pro- duction scheduling and control) enables the exchange of process plan data.

In many respects workstations are becoming more and more important for engineering applications like

CAPP because of the integration function and conve- nient modelling transformation. 3 This is especially important for large companies which demand a higher rate of utilization and multiple user terminals.

The programming method characterizes flexibility in adapting a system to application-specific facts. This mainly refers to company-specific planning proce- dures and data and to the possibility of improving the degree of automation. Some systems use decision table techniques to meet these requirements. 9

Looking at the customary programming tech- niques, it must be realized that, for several reasons, the application of decision tables and AI techniques (arti- ficial intelligence) will improve (Fig. 5). The main reason is the flexibility required of CAPP systems which is of outstanding importance especially regard- ing the constantly changing manufacturing technolo- gies. This is achieved on the one hand by decision tables that can be updated by the user himself and thereby be extended to other applications and on the

Fig. 4.

A d m i n i s t r a t i o n ~ o n of P l a n n ~ a n L ~ T a ~ I

L T,o':o.,.°,aooo o.,. I Iculation Data ~

,so [ ] [ ] [] ! cluing and Cor~rol

Structure of the CAPP system PC-CAP.

68 Robotics & Computer-lntegrated Manufacturing • Volume 10, Numbers 1/2, 1993

Programming Technique Advantage

conventional programming

application programming

• tailor-made, company specific solutions

• simple integration into existing environment

• wide planning knowledge for special processes

• short response times

decision • wide field of application tables (e.g. for assembly planning)

• no programming shells required

• updating by user

expert • company specific systems problem sotving

• flexible structure of knowledge base

Disadvantage

• requires a lot of development • fixed degree of automation • difficult to transfer

• limited field of application • requires extensive work

for adaption and extension • user needs programming

skills

• long response times • fixed structure of

knowledge base • insufficient clarity of

decisions

• extensive programs • powerful shells hardly

available • development and application

requires qualified personnel

Application Tendency

\

/ Fig. 5. Programming techniques for CAPP systems. ~2

other hand by expert systems which have a flexible, usually company-specific, knowledge base. The appli- cation of expert systems is basically limited because powerful shells are not generally available.12 The use of AI techniques will be discussed further in the following section.

3. FUTURE TRENDS IN CAPP DEVELOPMENT

Because computer-aided process planning is such a diverse field and involves various technologies it is not easy to predict future trends. However, future develop- ments in CAPP systems will particularly include the following items (Fig. 6):

• extension to new applications like assembly plan- ning,

• functional integration with NC programming and • the use of AI methods for decision making, • data integration with CAD by shared databases.

The extension of CAPP to other applications is already the object of research activities. In particular

CA'-D/C A--'P- ~ ...... bq p,anni~

I ~ ' ~ ~ o in=tegration wilh

Fig. 6. C A P P future trends.

the field of assembly planning has been neglected up to now. Because computer-integrated manufacturing (CIM) demands high quality and effective processing of planning data the results of assembly planning must also be integrated.

The steadily increasing automation of assembly causes increased complexity of assembly planning which requires efficient system support. Improved control systems for assembly will require detailed assembly planning with constant and reproducible results. Although the results of system support for assembly planning are still very limited, this applica- tion will be increasingly important. 13'14

As mentioned before in this paper, the functional integration of process planning and NC programming will progress in the future. This approach is based on the fact that detailed operation planning is necessary for conventional as well as for NC controlled manufacturing.12

A research project dealing with the integration of a CAD/CAM system and a knowledge based operation planning system for manufacturing forging dies has recently started at WZL (Fig. 7). The integration aims to reduce the NC programming time and to optimize operation planning. This will be done by extending a normal CAD/CAM system by technological NC func- tions for milling and grinding and integrating it with an expert system for operation planning which will suggest operations and the required tools. The system modules will be accessed via the same user interface and all data will be stored in a common database.

The use of AI techniques or expert systems for representing process planning knowledge offers the chance to automate further planning functions. 15 Al- though results from AI approaches are already pro- mising, there are various problems that prevent broad utilization in real production environments. The rea- sons for this are the complexity of the rules to be

69

Logic Representation

of Planning Data

• Preparation of Contour

• Support of Technology I I { p,.~';~'~,.,. I ( 3 D- NC-Mo~o~ ) Planning I L

[ ] * Generationg the~l L ~ Milling-Graphite [ ] Operation elan'~I~'L-pTOro~ssses ] HarOeneclSteel

• Generating a . . • Determine Tool Path t t No-Prog ram Ikc:oP, ,amo.t. J I Structure I J

! Fig. 7. Integrated operation planning and NC program- ming system.

acquired and the problem of knowledge acquisition. AI-based programs are also inefficient at calculating mathematical functions. Hybrid systems integrating conventional and AI-based techniques seem to solve some of these problems. 2'16'~7 Nevertheless, there is no doubt that if improved AI techniques are available knowledge based CAPP systems with high efficiency will be developed.

A more promising approach to CIM than current ones, which are mainly trying to interface separate systems, is integration by shared databases. This necessitates a common data model that contains both design and manufacturing information. Past research activities in this field started from process planning and concentrated on extending the data model to other applications. 2'5 These efforts led to several prob- lems and therefore a new approach to integrated modelling must be developed.

4. INTEGRATED MODELLING FORMS THE BASIS FOR FUTURE SOFTWARE

DEVELOPMENT The first feature-based prototypes of CAPP systems to be implemented revealed that the manufacturing task had to be modelled to meet special manufacturing requirements. The use of CAD modelling techniques turned out to be unsatisfactory. As described above, CAPP systems develop towards generative process planning using feature-based workpiece models which will become the kernel of integrated systems (Fig. 8). This indicates the high importance of integration with CAD via shared databases.

CAPP and NC programming system development originated from different starting points although they actually form a logical sequence of functions. There- fore NC programming is going to be a subfunction of specific CAPP systems, allowing the hierarchical de- composition of a manufacturing task from process plan to related operation plan(s) and further to related NC program(s). Development towards integrated CAPP and NC systems follows different directions, either extended CAPP "downward" or NC systems "upward".

Fig. 8. model.

Geometric Task l Definition

i manufacturing

features

\ i Information Model l ~

Representation of "~ Planning Results /

NC-program TM

~ocess l~a - V C I

oo,

~ l . - J - tool no.

CAPP state of the art and future development • W. EVERSHEIM and J.~SCHNEEWIND

/

Components of an integrated manufacturing

The development of an integrated manufacturing model should follow the development directions described. Furthermore, the following requirements must be fulfilled:

• support of all planning activities such as task description (workpiece modelling), process plan and NC program generation (hierarchical manu- facturing process modelling),

• allow the modelling of different workpiece and manufacturing domains,

• use of the same technique, i.e. use of features, for both workpiece and process modelling

• include company resource data in the model, • use advanced object-oriented modelling approach

to ensure optimized data management and • avoid hardware dependencies using standard data

formats.

To meet the outlined requirements a systematic ap- proach for modelling processes has to be worked out. Development work in this area has already started.~S

5. CONCLUSION CAPP systems are of outstanding importance for computer-integrated manufacturing and have recently been improved by using advanced technologies. But CAPP is still facing some important problems of integration. New approaches for integrated part and process modelling based on features are the key issue for an integrated CAD-CAPP-CAM environment and form the basis for future software development in the area of computer-integrated manufacturing.

REFERENCES 1. Mancey, J.: Choosing process planning software. Indus-

trial Computing Nov. 1990. 2. T6nshoff, H. K., Anders, N.: Survey of development and

trends in CAPP research within CIRP. Ann. CIRP 39(2): 1990.

70 Robotics & Computer-Integrated Manufacturing • Volume 10, Numbers 1/2, 1993

3. Alting, L., Zhang, H.: Computer-aided process plan- ning: state-of-the-art survey. Int. J. Prod. Res. 27(4): 1989.

4. Ferreira, P. M., Lu, S. C.-Y., Zhu, X.: A conceptual model of automated process planning for the machined parts domain. 22nd CIRP International Seminar on Manufacturing Systems, Enschede, The Netherlands, 1990.

5. Eversheim, W, Diels, A., Rozenfeld, H.: Changing re- quirements for CAP systems lead to a new CAP data model. Ann. CIRP 36(1): 1987.

6. Eversheim, W, Marczinski, G., Rozenfeld, H.: Require- ments on interfaces and data models for NC data transfer in view of computer-integrated manufacturing. Ann. CIRP 38(1): 1989.

7. Rozenfeld, H,: Rechnerunterstiitze Arbeitsplanerstel- lung ffir komplexe prismatische Grol3weksfiicke. Disser- tation, RWTH, Aachen, 1988.

8. Eversheim, W., Schulz, J.: Survey of computer-aided process planning systems. Ann. CIRP 34(2): 1985.

9. Eversheim, W, Cobanoglu, M., Luszek, G.: Baustein fiJr die Integration--Stand, Entwicklungstendenzen und SchnittsteIlen yon CAP-Systemen. Industrie-Anzeiyer 85: 1988.

10. Eversheim, W., Luszek, G.: Rechnergestfitzte Arbeits- planung mit dem PC. Arbeitsvorbereitun9 25(11): 1988.

11. Witte, H.: PC in der Arbeitsvorbereitung die Planung im Griff. Arbeitsvorbereitun 9 26(6): 1989.

12. Boll, G.: Enwicklungstrends von Systemen der rechner- gestiitzten Arbeitsplanerstellung Vortrag im Rahmen des "CIM-Management Workshops CAP". Winterthur (CH), 1988.

13. K6hler, F., K6nig, D.: PIA ein wissensgestiitztes Pro- gramm-system zur automatischen Erstellung yon Mon- tagearbeitsplanen. Werkstattechnik 78: 1988.

14. Eversheim, W., Luszek, G., Schulz, J.: Arbeitsplanerstel- lung fiir die Montage. lndustrieanzeiger 108(20): 1986.

15. van't Erve, A. H.: Generative computer-aided process planning for part manufacturing--an expert system approach. Dissertation, University of Twente, 1988.

16. Taiber, J., Zfist, R.: Knowledge based process planning system for prismatic workpieces in a CAD/CAM environment. Ann. CIRP 39(1): 1990.

17. Ziist, R.: Wie welt l~il3t sich die Arbeitsvorbereitung automatisieren? Management Zeitschr. 59(11): 1990.

18. Eversheim, W., Cremer, R.: lntegrierte Operationsplan- ung ffir komplexe Werkstficke. Industrie-Anzeiqer Nr. 91/92, 1990.