Keynote Papers

Evolution and Future Perspectives of CAPP

Professor Hoda A. ElMaraghy (I), McMaster University, Canada

With contr ibut ions from: E. Agerman (2), B. J. Davies (l), W. H. EIMaraghy, W. Eversheim (I) , D. G. Halevi (I) , I. H a m (I), H. B. Jasperse, H. J. Kals (I), A. Y. C. Nee (l), G. Sohlenius (l), V. Tipnis (2), H. K. Tonshoff (I),

C. A. van Luttervelt (I), R. Weill (I) , H. P. Weindahl (I) , F. Javane (1)

ABSTRACT:

Modem manufacturing is characterized by low volume, high variety production and close tolerance high quality products. Computer Integrated Manufacturing (CIM) is recognized as an effective platform for increasing manufacturing competitiveness. Computer Aided Process Planning is an essential key for achieving CIM. The integration of design, computer aided process planning (CAPP) and production planning and control (PPC) is becoming essential especially in a concurrent engineering environment where many product life cycle factors are of concern. An overview of the major development thrust in CAPP is presented along with some of the evolving trends and challenges such as rapid, generic, dynamic andor distributed process planning. Related issued of quality and evolving standards are also discussed.

KEYWORDS:

Computer-Aided Process Planning, Computer Integrated Manufacturing, ProducVProcess modelling and planning

1.0 INTRODUCTION

Recent advances and interest in integrated manufacturing, producVprocess design, life-cycle considerations and concurrent engineering has given process planning a very prominent role as one of the effective agents for achieving the desired seamless integration between the various modules in a CIM environment.

In today's economic climate, companies are realizing that responsiveness to market demands and adaptability to changing conditions, while delivering high quality products and services at competitive prices, are the hallmarks of a successful enterprise in the nineties and the survivors into the twenty first century. Close coordination of product design with manufacturing processes, systems design and increased coupling between process and production planning and control are becoming prerequisites for achieving competitiveness in today's global economy. Effective process planning can provide the glue for these intertwined activities.

The past few years have seen great advances in the functionality of process planning systems and the tools used to achieve it, widening the scope of applications, enhancing links with other activities and increasing awareness of the need for better interaction with and support for the human process planner. The activities within %IRP have reflected these changes, and in many cases, pioneered the new developments. The objectlve of this keynote paper is to assess the evolution of various CAPP approaches and techniques, reflect on their proliferation and effectiveness in industrial applications and explore the future perspective and research directions. This paper will not survey or evaluate existing CAPP systems, rather it focuses on identifying important concepts, significant shifts and required new developments. However, the included list of references would be helpful to those seeking to review various CAPP systems reported in the literature.

2.0 THE CAPP WORKING GROUP WITHIN ClRP

This keynote papercomesat a time when the activitiesof the CAPP working group have flourished, matured and attracted active participation by a large number of ClRP members. Therefore, it is appropriateto begin with a brief historical note on itsevolution (figure 1).

The CAPP Working Group has a long history which began at the 1966 General Assembly in Paris. This was the year of the foundation of STC"0 (Optimization) with E.M. Merchant as the first Chairman. At the same time, R. Weill proposed to establish a working group on "Optimization of Machining Conditions by Computers"which can beconsideredasthe ancestorof the present CAPP working group. Initially, this group was involved with cooperative research on the validity of the different algorithms proposed for the optimization of machining conditions. A standard model for optimizing the turning process parameters wasdesigned and unification of the terminology in the field of machining optimization was undertaken. During the same period, the philosophy of Group Technology (GT) was pursued and an

Figure 1 :Evolution of the CAPP Working Group within ClRP .

international survey of the topology of workpieces was conducted. The mainconclusion of thestudy wasthat GroupTechnologyshould also include the influencesof design, work planning and scheduling in addition to the geometric considerations.

development of numerical control (NC) languages. The ClRP working group undertook cooperative studies to evaluate and compare a number of existing languages and to contribute to their unification. A keynote paperon thissubjectwasgiven by R. Weilland C. Sauvaire in Warsaw at the 1971 ClRP General Assembly. Since 1970 the activities of the working group were diversified. Studies were conducted and reported in the areas of the economies of machining, multitool and multispindle machining, machining information centers and data bases.

In 1976, the working group adopted the name, "Process and Operation Planning", which reflected better the domain of its activities. It undertook a worldwide survey of existing process planning systems and future trends. A keynote paper presented at the General Assembly in 1982 in Bruges 111 attempted to identify subjects suitable for computerized process planning and reviewed existing systems for their capabilities and limitations. A follow up survey was reported in a 1985 keynote paper 121.

The subject of computerized process planning became a central activity of the working group and its name was changed to CAPP (Computer-Aided Process Phnning) as proposed by I.Ham who assumed its chairmanship in 1986 at the General Assembly in Israel. AspecialseminaronCAPPwasorganizedin Parisin January 1985 with presentations of research papers by 15 members from 8 countries. It was followed by a ClRP Seminar on Manufacturing

The years 1967 to 1973 were also concerned Mth the '

Annals of the ClRP Vol. 42/2/7993 739

Systemsdevoted to CAPP in 1987at Pennsylvania State University 131 with strong participation of universities and industry from the United States. The use of artificial intelligence techniques for computerizing process planning was strongly emphasized and illustrated by examples. A keynote paper on CAPP-Past, Present and Future was presented by I.Ham and S.C.-Y. Lu for the ClRP General Assembly in Tokyo in 1988 (41. This was followed by a workshop on CAPP organized in Hannover (Germany) in September 1989 with 12 papers and about 50 participants (51. A survey by H. K. Teenshoff on CAPP System developments was published in the ClRP Annals, Vol. 2,1990 [6]. A ClRP Seminaron ManufacturingSystemsheldinTwente(theNetherlands)in 1990[7] wasalso mainly devotedto CAPP with 34 paperspresented and 106 participants including 7 representatives of industry. R. Weill and G. Halevi organized a survey on the objectivesof CAPPand presented their first results in 1992 at the ClRP Seminar on Manufacturing Systems in Copenhagen (Denmark). An interesting conclusion of this survey was that process planning should not be treated independently of production planning. Many papers in the Copenhagen seminar [S] reported on integrating CAPP with other applications in concurrent engineering environments and the keynote paper by H. ElMaraghy and W. ElMaraghy emphasized the need for bridging the gap between CAPP and production planning 191. Anothersurvey among the Membersofthe Working Groupabout theiractivitieswascarriedoutin 1992 byl. Hamandupdatedin 1993 [ I 01. ltshowedclearly the widening scopeof CAPPapplicationsand its integration with both design and shop floor control.

As can be seen, the history of the CAPP working Group closely mirrors the evolution of ClRP in the last 25 years. It began with work on narrowly focused optimization of specific parts of the manufacturing system (e.9. machining operations, group technology, data banks, and NC programming) and ended up with a strong emphasis on the optimization of the whole manufacturing system, including product design, production control and management. Cooperative efforts should now continue to firmly implement this trend in both production engineering practice and research.

3.0 EVOLUTION AND STATE-OF-THE-ART IN CAPP

Planning is concerned with generating the set of steps required to reach a specified goal, within given constraints, while optimizing some stated criteria. Manufacturing process planning seeks to define all necessary steps required to execute a manufacturing process which imparts a definite change in shape, properties, surface finish orappearance onapartora product (figure 2). A complete set of these plans would cause the materials to be

PROCESS PLANNINQ ROLE AND ISSUES

Figure 2. The Role and Issues Involved in Process Planning

transformed into a functioning product ready for use, based on the product functional requirements, specified by the product design andcaptured by the product description. Hence, it can be seen that manufacturing process planning applies to a wide variety of manufacturingprocessesincluding metal removal, casting, forming, heat treatment, fabrication, welding, surface treatment, inspection andassembly, etc. Until recently, research anddevelopment efforts have focussed on CAPP applications in metal removal, particularly NC machining, almost to the exclusion of other applications. However, the strong drive towards integrating all the manufacturing functions has emphasized the need for applying CAPP techniques

to many manufacturing processes and encouraged developments in that direction.

A number of factors affect the nature of process planning and its outcome. At the highest level, planning may seek to select the most suitable technology forproducing afeature, a partora product (i.e. metal removal, material addition, forming orjoining.. etc.). This may be called genericor conceptual planning, the outcome of which is a conceptual ( or abstract) plan. Planning may concentrate only on one domain (eg. assembly or sheet metal processing ) or may consider several different applications and hence would be called multi-domain process planning. The amount of detail in analysis, input and output of process planning also determines whether it is Macro-Planning (i.e. concerned mostly with sequencing) or Micro-Plannina (which determines detailed Drocess Darameters,

quired tools Gnd setups, process time, resources, etc.) as seen ~ure3.The planning approach itself, thedataand knowledge USE

HIERARCHY OF PROCESS PLANNING

PUNNING ACTIVITY L M L PUNNING OUTF'UT Orwd

Figure 3. Types and levels of process planning activities and their outcomes

the modelling and analysis techniques all determine whether process planning may be called variant, semi-generative, generative, intelligent, automated andlor interactive.

lnvestmentsinautomatedproduction machineryandsystems has increased steadily in the last fifteen years. These machines place high demands on process planning and control as well as programming resources. While productivity improved due to increased hardware automation and quality improved due to increased accuracy and repeatability, the anticipated increase in flexibility and adaptability did not materialize due to the increased preparatory work which must be done before actual productron takes place including process planning and programming. The automation of process planning presents many challenges as it involves a multitude of conflicting criteria and competing objectives and requires a great deal of expertise and knowledge which are not easy to model and codify. Hence, the early work in CAPP focused on isolated portions of planning activities such as selection of suitable tools, calculation of machining parameters. generation of cutter path, etc.

Thevariant approach marksthebeginningofcomputer-aided process planning systems, and is basically a computerized database retrieval approach. In this typeof CAPP system, partsare grouped into part families, a unique code is generated for each family, and a standard process plan for each is developed beforehand. The planning of a new part is performed by identifying and retrieving existing plans for similar parts and making the necessary modifications to suit the new part 111-171. Semi-generative and generative CAPP systems were the next generation wherein the "standard process plan" concept was replaced by a computer system capable of making part specific decisions aboutthe operation to be performed to produce a part. In this type of CAPP systems, decision tables or decision trees are described by GT coding and classification schemes orspec.ialized partdescription languages [18-21]. The need forapartdescnption scheme suitable for automated process planning lead to the use of CAD models, mostly with user's interaction, for selecting the featuresof interest andproviding somedata[22-24,36].The useof knowledge4ased systems and Artificial Intelligence techniques was the next major development in the direction of generative process planning [25-44, 891. Examples of knowledge-based process planning systems [ex. EXCAP, GARI, TOM, SIPP, SIPS, TOLTEC, Turbo-CAPP, XPS-2, CMPP, DCLASS, HCMAPP and

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others] are discussed in [118]. Automated planning activities are invariably faced with the problem of exploding search space when the number of combinations and permutations of choices grows to the point where it takes a prohibitively long time to reach a feasible solution (if any) let alone an optimum solution. A good combination of algorithmic procedures and heuristics is essential for obtaining a good process plan.

4.0 INDUSTRY PERSPECTIVES ON CAPP

A number of CAPP systems have been commercialized and implemented in industry over the years in addition to those proprietary ones which were developed by specific companies for their internal use.

A few examples of recent systems include : PART [4547] and PARTS [49], AVOPLAN and CHAINPLAN [6], DTWCAPP [48], EXCAP [23], XPLAN [26], METCAPP [50]. No attempt is made to include a comprehensive list here, but the bibliography includes references to many more

The newer systems adopt many advanced techniques and approaches such as feature-based modelling, object+riented programming,effectivegraphicaluserinterfaces, technologicaldata bases and utilize advanced computing methods including expert systems and artificial intelligence. They are making good use of recent advances in computer hardware and software and endeavor to be more user-friendly and many attempt to establish links with oneandmore aspectsoftheoverall manufacturing activities. In spite of recent successes, the focus remains on metal removal, several questions remain unanswered and many issues must still be resolved. It has been observed by many that the implementation of CAPP systems in industry lags behind the rate of development of new systems and the introduction of new ideas in the field.

According to Alting and Bang [25], in spite of the fact that a tremendouseffort has been made in developing CAPP systemsand that in the last two decades many CAPP systems have been developed, the effectiveness of these systems is not fully satisfactory. CAPP as a main element in the integration of design and production has not kept pace with the development of CAD and CAM [25]. This situation has lead to some doubt about the current state of the research and implementation of process planning.

As stated by Prof. 1. Ham [la]: "..., the primary reason for this dilemma is the lack of correct models of process planning parts, planning methodologies, processes and equipment. There are two aspects of these models, the conceptual model and the implemented or the computer model. It should be pointed out that finding a conceptual model for process planning is very difficult not only because of the complex interaction between process planning and other activities in a manufacturing enterprise, but alqo because of the distinctive challenges of planning within different types of industries.. . .

Another difficulty is due to the fact that the scope of process planning is constantly changing due to the new demands in product development practice. For example, the recent development in simultaneous engineering concept which calls for more concurrent activities between product and process design lead to some interesting implications in traditional process planning activities. Another interesting example is the design for manufacturability concept which stresses the feedback from production to design. This concept basically changes the traditional role of prqcess planning, as a one-way bridge between design and production, to a two-way communication channel between designers and production engineers. This bi-directional information Row requires a clear structure of process planning tasks".

In spite of the benefits promised by the various developed CAPP systems, their adoption by industry is still painfully slow. Today, almost 85% of all process plans are still created manually, and detailed optimized plans are rarely produced. Static routing sheets whichdo not consideractual resources utilization, are mostly produced manually. Today, when companies use CAPP systems, it is mostly done in isolation from the product design process as well as the production planning and control activities. Careful assessment of this situation and the reasons behind it is essential to illuminate the discussion of the future research anddevelopment directions. The following are some observations made by several colleagues who had experience with working with industry on applying CAPP systems:

Users are discouraged by systems which require much time and effort to prepare and enter the required data, are cumbersome to use and take a long time to produce the answers.

Most systems are black-boxes because their internal heuristics and algorithms are not known or cannot be changed by the user. Practitioners are not willing to use black-boxes because they do not understand them. Users lose confidence in the systems if the answers are not consistent with gained experience or are not well explained. They become even frustrated if they are unable to override or modify some of the decisions made by the system. As the CAPP systems become more sophisticated, they take longer to install in a company. Experience shows that industry does not tolerate systems which take more than half a year to become fully operational. Users prefer CAPP systems which which are flexible, can be adapted to their company's products, procedures and practices and can be adjusted to fit different planning scenarios and managerial goals. However, if such customization becomes a significant task, they quickly lose interest. Most CAPP systems focus on simulating and automating procedures previously done manually. Tools which focus more on synthesis, rather than analysis, would be of more assistance during the decision-making process. Present CAPP svstems onlv offer Dartial solutions. Thev are limited in scope and are isoiated fr$m the rest of the manufacturing functions. They offer poor or no interfaces to functions such as order management, engineering and design, capacity planning, scheduling, tool management, material management, quality control and purchasing as well as existing data bases. Users prefer to interact with the CAPP system using manufacturing oriented language rather than infomation science and A1 jargon. Process planners are often people who were first machine operators with limited education who require a friendly interface. The task of populating knowledge bases and data bases with information can be daunting. Easy access to existing data bases, catalogues and effective knowledge acquisition tools is needed. It was observed that the use of todays CAPP systems generation results in process planners time saving of less than 15%. Companies must balance the benefits of CAPP with the total cost incurred including the recurring cost of usage (i.e. entry and manipulation of data, rules and knowledge) in addition to the initial cost of purchase, installation and training [58]. New trends are developing as a result of increased subcontracting by large manufacturing enterprises compared to manufacturing the parts in house. This will have profound impact on who does the process planning. Suppliers are becoming more responsible for process planning in their shops and for implementing quality assurance procedures according to IS0 9001-9003. CAPP systems suitability to the knowledge and computer literacy of these new targeted users will be crucial. Production disruptions occur on the shop floor due to a shortage of resources (machines, tools, material, operators, etc.) and bottlenecks. Foremen'change the route sheets to meet production demands; however, this is done locally without

*

complete knowledge of the effect on the overall operation of the factory and often leads to higher costs. Although some of the day to day production pl.anning problems can be solved by scheduling techniques, it is apparent that rationalized alternate plans are needed in many cases to cope with the dynamic situation on the shop floor. The lack of communication between process planning and production planning obviously leads to higher costs and is a serious obstacle to achieving effective integrated manufacturing systems.

5.0 MODELS AND STANDARDS

The central role which process planning plays in integrating various product and process models and activities is illustrated by theI-DEFOmodelofprocessplanningshownin figural Eachentity in this graph contains vast amount of information, knowledge, proceduresand techniques all of which are needed during process planning. The complexity and intertwined nature of these models, namely the part model, the product model and the process model, emphasizes the need for standardizing the representation and exchange of information and knowledge contained in these models.

5.1 STEP

lntemationalefforts are continuing to define a standard forthe exchange of product model data - STEP as well as related

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I

Tools. Set-ups 8 Resources Machine Instructions

Process Time,

I CONTROL - Technological

Capabilities Resources Process Production

-b

+ +

t t - MECHANISM

:igure 4. IDEF-O Representation of Process Planning Activity

C U T U T

) P

Figure 6. Casting Application Protocol Planning Model (Paul, G.[113])

application protocols standards. A standard for a process plan model is still under development. The approach taken is to devote a partial model within the Integrated Product information Model (IPIM) to the process plan. The process plan model contains a unit forall the information required to represent process plans anda unit for related process plan activities (e.g. relevant macros). The process plan model references other models, such as form tolerance and resources models within IPlM and hence,, avoids duplicate storage of the same information. Part 49 of IS0 10303 [5 1,551 indicates theinformation necessary tospecify theoperations usedto realizeaprocess. Thisincludestherelationship between the operations in the process, the relationship between the processes used to realize a product, resources and their properties, relationship between a process and a product, specification of a process plan and alternative process plan definitions. A process plan model does not specify any particular process, but defines the elements to exchange process information.

Part 213 of IS0 10303 is an application protocol (AP) which addresses the exchange activity and sharing of computer interpretable numerical control process plans for parts machined from castings and forgings. It specifies the data contained in the process plan, as opposed to the data necessary to perform the process planning functions, asshown in figure 5. More specifically

NC Process Plan Appllcatlon Protocol Data Plannlng Modal

SEOUENCES

IS CONSTRAINED BY

Figure 5. Data Planning Model ( IS0 10303 [51] )

it specifies information contained in NC process plans forprismatic and turned parts (instructions, sequence and resources), information to support in-process inspection, to allow exchange of NC process plans between dissimilar CAPP systems and allow regeneration of NC process plans.

The application activity model (AAM), shown in figure 6, provides graphical representation of these processes and information flows. The efforts to develop standard structures for representing and exchanging process plans will contribute significantly tosmootherintegration betweenvariousmodules within CIM. It is clear, however, from the state of development of these standards and application protocols that more attention must be

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PROCESS PLANNING FOR CASTING

Cast Product Procma J E 2 Features

Casting Geometly

Tolerance Process - I Surface Flnlah I

given to other CAPP applications in addition to metal removal. A large number of industrial companies are contributing to the developmentof the Standardsandseveral softwarecompaniesare already developing application based on them.

TRENDS IN CAPP

6.0 INTEGRATION OF CAPP AND PRODUCT DESIGN

6.1 Concurrent engineering

Theconcurrentengineeringandtheemphasisonincluding life cycle consideration necessitate a two way interaction between product design and process planning. It is no longer sufficient to ensure an effective flow of infomation from design to process planning to provide the data and knowledge necessary for creating an efficient process plan. It is becoming essential to feedback information from process planning to assist the designer at an early stage in assessing the various design features not only from a functional point of view but also regarding manufacturability, assemblability, processing time and cost. A large percentage of a productcost is committedonce itsfeatures, material, tolerancesand surface quality parameters have been selected at the design stage [52]. Many CAPP systems determine one or more of these factors [70]. What is missing are the computing environment, tools and techniques which allow this information to be available at the designers finger tips and in a usable format to assist in decision making regarding the design parameters. If the designer realizes early enough that some features require expensive fixturing, or demand special toolsandelaborate processes, it would be possible to try other alternatives. Research in enabling technologies for concurrentengineering is progressingat an accelerated rate and the desiredcloserintegration between design and process planning will benefit from its results [52]. Research on enabling platforms which may facilitate this type of interaction has been reported [53].

6.2 Rapid Proceo Planning

The designer must consider many factors in order to refine a product description into a final and realizable product model. The cost, feasibility and ease of manufacture are among the important factors which influence the design decisions. This feedback to designers must be quick in order not to impede the real time and interactive nature of the design process. Therefore, there isaneed for preliminary and simplified process planning, to precede the detailed planning, where initial manufacturability evaluation analysis, simple cost models and/or expert rules may be used to provide aquickassessmentand producibilityadvice to thedesigner [54]. It is important that the advice to the designer points out those design aspects or features leading to complex process plans or excessive production cost. It would also be very helpful i f this initial producibility analysis suggested ways of alleviating the problems, although this part should probably be best left to the designer’s ingenuity and experience as it requires extensive knowledge and elaborate reasoning.

6.3 Manufacturable Design Transformations

Another approach for linking design with process planning, with the aim of sensitizing the designer to the manufacturing

feasibility of chosen forms, is the notion of manufacturable objects [56,57]. It is based on two facts: i) that the design transformations capturedin the CSG treeof anobject modelled usingsolidgeometric modelers can be related to some process planning steps (e.g. incremental volume removal), and ii) that multiple CSG trees exist fortransforming an initial shape (stock material) to the final product depending on the boolean operators used, hence leading to alternate process plans. Some of these transformations may not represent any feasible manufacturing steps while others are manufacturable. A system which contains a library of manufacturable objects was implemented in the domain of ml

nova1 bymilling(figure7). Itusestheseobjectsasmanufactui

The set ol available Manufacturabh Ot+cis

A Manufadurable

Manufadurable Obi-

&? aDdv

Two dinerent Manufacturing Trees

Figure 7. Manufacturable Design Transformation (Delbressine, et. at. [56 & 571)

features to be appliedat the design stage to obtain the desired final shape while guaranteeing manufacturability. The system reduces the time required for process planning and allows more consistent process plans by virtue of using the previously analyzed manufactured objects and their detailed process plans as design features. Using this approach the manufacturability of a proposed design can be checked further for reachability, feasibility of position and orientation tolerances as well as setups.

6.4 Generic Process Planning

The manufacturing domain ortechnology is usually assumed at the start of process planning. A planner would determine initially that acertain cavity would be produced by EDM rather than milling, orthatanearnetshapeformingorcastingwould beusedtoproduce the initial component rather than machining it from a block, or that a part would be made by joining two pieces rather than one, etc. as illustrated in figure 8. Once these initial decisions are made, the evaluation of the feasibility andeconomical and technological merits of alternative fabrication methods are usually ignored.

Generative planning is concerned with the initial choice of the manufacturing technology or equipment to be used and the assessment of feasible alternatives. The results of this reasoning is fedbackto thedesignertoassistin thechoiceofappropriatedesign features at an early stage. The approach is based on the manipulation of the boolean operators used in CSG modelling to yield alternate object construction methods. This, combined with a setofexpertruleswhichcapturetechnological knowledge regarding materials, process capabilities, attainable equipment accuracy and repeatability, etc. form the basis for a generative high level process planner implemented recently 1591. This novel approach to C,APP is based upon a set-based design. The sets contain a number of geometrical, and other properties. These sets are related through the use of boolean equations. As an example, Constructive Solid Geometry (CSG) designs are a sub-set of this representation. The

,

Very thin walled large diameter Sharp corners Very narrow,

very bng hole OMect ...

objects which should not be machined from solid stock

Figure 8. Examples of reasoning used in high-level generic planning

design may then be converted to an equation form which serves, initially, as the basis for high level planning. Certain forms of a Boolean expression can be directly mapped to certain forms of manufacturing operations using template matching. After finding known equation patterns, a number'of rules are selected for condition comparison. If the conditions of a rule are satisfied then a conclusion is made regarding the manufacturing technology to be used. This reasoning process continues until all the equations are exhausted, and the plan is complete. Therefore, the final design not only contains the original design information, but also information aboutthe state of the product in each stage of production,alternative manufacturing operations and estimated costs for each plan Step. Examples of the reasoning logic used in this system are shown in Fig. 9.

This approach provides fast advice to designers early in the' design process and is closely coupled with the product modelling activities. Once the manufacturing technology, and the type of equipment or process have been chosen, further detailed planning is carried out as usual.

6.5 Features & Process Planning

The subject of features and their role in product design, process planning and many other activities spanning the whole product life cycle has generated much interest, heated discussion and even controversy in recent years 160, 72-76, 99, 1121. Many researchers talked about design features, functional features, form features,manufacturingfeatures, somecalledthemmanufacturable objects and others simply refer to them as parametric templates (reminiscent of the good old macros in APT). No attempt will be made, in this paper, to arrive at a unified definition or conclusions regarding features representation or attributes. However, some discussionof their use and relevance toprocessplanningisinorder.

During the highly creative conceptual design phase, the designer relies on both intuition and accumulated knowledge and expertise to select design features which would achieve the desired functions, by themselves or in relation to other features within the partorproduct. Once majorfeaturesare decided upon, othersfollow for the purpose of linking the major features together or to facilitate their manufacture.

One shoulddiff eren tiate here between functional featu res and form features. Form features refer to recognizable shapes which cannot be further decomposed, otherwise, they will reduce to meaningless geometric entities such as lines, points and surfaces. Form features, while affecting manufacturing processes, may or may not by themselves have a functional purpose.

Higher level functional features (e.g. keyseats; fillets, chamfers, splined shafts, threads, etc.) are more natural to use by designers than geometric abstractions and often form features. These macro functional features may be further decomposed into simpler or micro form features for the purpose of geometric representation or manufacturing task planning. However, such decomposition should be transparent to the designer as shown in figure% Some nonfunctional features may be deducedand created interactively or automatically using expert knowledge, to join functional features or facilitate their manufacture. For example, undercuts may be needed to make external thread cutting feasible

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I

Figure 9. Boolean Algebra used for defining alternate Processing Technologies

( EIMaraghy, W. H. and Jack, H., 1591 )

in some situations and rounded comers would be used to facilitate assembly of components against right-angled shoulders.

Additional knowledge required to convert design specifications to manufacturing steps (i.e. process planning) is predominantly domain specific. However, process planning is also dependentontheinherentattributesoffunctionalfeatures.Ashaffs function, size and method of support suggest a certain fit class and consequently, specific dimensional andlor geometric tolerance requirements. Such attributes (whether deduced, inherited or specified) must be included in functional features definition, as well as known heuristic or basic knowledge about expected behaviour, relationship with otherfeaturesormanufacturingaltematives(figure 10).

Design'.Functional Features Form Geometric . Features Primitives I

I *ilrpbpm I Figure 10. A Mounting Feature of An Air Cylinder

(EIMaraghy, H.)

Asystem which usesthisconceptofdesigningwith functional featureshas been implemented[60] andiscalled IPDM-Intelligent Product Design and Manufacturing System. It uses a hybrid CSG and &rep geometric mcdeller and contains a library of functional features as well as provisions for users to specify their application specific features using the Product Description Language PDL or interactively. It maintains a hierarchical structure of the product, subassemblies, parts, functional features, manufacturing features and geometric entities. It also captures the various features attributes both defined by the user or inherited (figure 11). Interference between features (afteradditionordeletion) ischecked using built-in rules or interactively with user's assistance to ensure the validity of the resulting product model 1611. This modeller is integrated with several process planners including an assembly

I

Figwe 11. Fundionel Features and Their Attributes (ElMaraghy, H.)

planner, a robot task planner, a CMM inspection planner and a multi4omain reactiveplanningenvironment(RPE)asseen in figure 12. '

PARTisanotherexampleofafeature-basedcomputer-aided process planning system for NC metal removal [45]. It uses the concept of features extraction rather than design with features. PART is a generative CAPP system which can automatically generate NC part programs, instructions and auxiliary information forthe manufacturing of small batches. It is designed for both on-line and off-line planning of processes and operations for machining centers. ltcan handleawidespectrumofcomplexproductandblank geometries. The system can interpret product and blank models (B-rep) automatically and can also select the resources needed to produce the parti.e.: machine tools, jigs 8 fixturesand cutting tools. It deals with the selection of set-ups, machining methods and sequences and the calculation of taol paths and cutting conditions. Limitations of the resources and the capacity of the workshop are taken intoaccount. The requirementofefficiencyandadaptabilityof the planning method to variety of manufacturing cultures has resulted in a system design based on flexible sequencing and parallel execution of process planning functions. The PART'S system architecture allows customization to the characteristic needs of a given company. Under normal conditions a process plannerdoes not have to interfere with the system, but an elaborate user interface provides the possibility to monitor and control the decision making process. PART is being used in industry and is availabfe commercially.

A collaborative effort between Europe and North America resulted in a feature-based generative CAPP system called Design-To-Manufacture (DTWCAPP) for metal removal NC application 1481. The system is also being used in industry and is available commercially. It is based on the MetCAPP system and. contains the Metcut technological data base. It also includes a process plan editor, 40 manufacturing features library and modules for selecting the best cutting conditions and tools as well as process time and cost calculation.

Many more feature-based CAPP systems exist, however, a reviewof allsystemsis beyondthe scopeofthispaper. Areasonably comprehensive references list is included to assist those interested in surveying them.

In summary, features can capture both the design intent and relevant manufacturing knowledge. Process plan segments may be associated with the features represented in the data base for future use. Features interactions must be checked and any necessary alteration to the original process plans, as a result of this interference, should be implemented. This approach can lead to effective incremental process planning. Any feature library in any system can never be complete, therefore, easy procedures and tools for introducing user defined features is essential for added flexibility and adaptability.

7.0 INTEGRATION OF PROCESS PLANNING AND PRODUCTION PLANNING AND CONTROL

For small batch manufacturers of mechanical parts the shortening of the manufacturing cycle, better adherence to schedules, increased flexibility of production and a more reliable determination of actual manufacturing costs are the most important issues. A significant rationalization potential in the informationchain from CAD to CAM can be identified in process planning. A reduction of throughput time in the process planning department can significantly decrease the total throughput time from design to manufacturing. Time reductions can be achieved in three areas of process planning by: i) supporting the process planner by transferring technology information from a data base, ii) developing an automatic process planning system, and iii) automating the transfer of workpiece data from CAD systems to process planning systems.

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FRAMEWORK OF THE INTELLIGENT PRODUCT DESIGN & MANUFACTURE SYSTEM (IPDM)

I Design Synthesis & Design Constraintsl

0

Feature Based ModeUer - Hierarchical product structure -Tolerance Spec. Interface -Standard Components Selector : - Disolav Interface

Analysis Packages

- Optimization

Functional Design Fenlurrs Library

Reactive Planning

Environment

+ c .lr .lr + Assembly Robot FMS Inspection Sequence Grasp Expert Desi n Planning &

Generation Planner Synthesis BT Simulation (GAPP)

Robot Task

Slmulatlon

Figure 12. Framework of the Intelligent Product Design & Manufacturing System (EIMaraghy, H., [SO])

7.1 Bridging the CAPP-PPC Gap

Computer aided process planning (CAPP) and production planning andcontrol (PPC), also known as scheduling, today remain essentially separate activities. Duringprocess planning the product design is converted to a list of operations and resources required to produce it, while during scheduling process plans for a number of products are considered together [68,69]. Also CAPP is essentially time independent, while PPC is necessarily time dependent. There are several reasons forthe lackof compatibility between CAPP and

. PPC which relate either to the functionality of these systems or to their use of data [9].

Jhe Functional GaD; At present, only single domain process planners are available (e.g., for metal cutting). They produce detailed steps and parameters required to manufacture features within a part (e.g., holes, slots). Such micro plans must be pieced together to form a process plan for the whole part. The produced process plans represent a fixed linear sequence of steps and resources to be used foreach. Since these planners try to optimize the process, the besttools andmachinesarealwaysselectedduring planning which leads to chronic bottlenecks. Other feasible alternative resources are not considered. The resources database for process planners is static and usually is not updated to reflect workshop status.

While available process planners focus on operations performedon single parts, production planning and control systems deal not only with multiple parts but also with multiple products to be manufacturedwithin thesamesystem. PPC systemsadoptaglobal view and, therefore, require macro plansforthe whole productwhich often involve operations in mixed domains (e.g., casting, cutting, forming, assembly). The objective of PPC is to optimize material flow, machine utilization and maximize throughput to meet production targets. Resources are frequently aggregated logically and combined into capacity groups for the purpose of capacity planning and load balancing. Available schedulers can only handle linear sequential plans. They may also consider additional resourdes, besides toolsandmachines, including human operators with different skills, material and time. WeeWy and monthly schedulesare usually developed. However, shortages of resources occur, leading to unexpected dynamic bottlenecks which disrupt production. Dependingonthe severity ofthese bottlenecks, revised routings and schedules may be required for implementation in the

next shift or next day. Alternate process plans may also be needed to cope with the situation while localizing the impact of the overall production.

Jhe Data GaD: While both CAPP and PPC systems use the same resourcesto perform the plannedtasks, thedetailedattributes anddefinitions required foreach system aredifferent. In addition, the data format and representation structure are also different. It is not uncommon for CAPP and PPC to use two physically different databases. Attempts at integrating both systems must deal with these differences in data type, content and format. Additionally, any dataupdates, due tochangesin resourcesstatus, mustbecarefully synchronized between the two systems. Today's available PPC systems cannot handle realtime resource shortages and actual utilizationdata, norcan they respond to thesechangesdynamically.

The above discussion illustrates some of the data, temporal andfunctional issuesleading to theexistinggapbetween CAPPand PPC. There isa clearneed to bridge thisgap, however, these basic differences indicate that an effective integration is not a trivial task. Three approaches for bridging the CAPP-PPC gap have been researched 191. These are:

7.1.1 Global Integration

The first approach is a high-level integration of functions and CIM modules which can be called a "global integration scheme". Each CIM module (CAD, CAPP, and MRPII) is allowed to maintain its own database and an updating scheme is devised. This method isvery dataintensive, resultsin theduplicationofdata, anddoesnot address the need for non-linear plan representation which considers actual and constraining resources ad events. The manufacturing systems' "events" (e.g., bottlenecks, etc.) are also not considered. Instead, the events relate to each individual data record, not to the status of the modules in the system.

7.1.2 Unification

Thesecondapproach isattheotherendofthespectrum, and proposes complete merging of planning and scheduling where CAPP and PPC become one system. Their representation and structure would be common, e.g., using Petri-nets to model logical and temporal relationships. FLEXPLAN (ESPRIT Project 2457) is a system being developed in that direction [62-64]. However, the

745

issues of real-time events and related feedback from PPC to CAPP in response to shop floor "disturbances" and the way for CAPP to replan were not considered initially.

Due to the large scale introduction of NC and CNC machine tools, process plans and their associated NC-programs have become very machine specific. Reallocation of orders to other machines on short notice becomes virtually impossible. Consequently, the actual utilization of machines is already significantly determined at the early stage of process planning. To meet the flexibility requirements from workshop control the process plan itself has to be more flexible. This can be achieved by a double strategy: 1. Introducing the concept of non-linear process plans which capture

feasible manufacturing alternatives, provide more flexibility to workshop scheduling and help in the evaluating the impact of rescheduling decisions.

2. Feeding back machine loading information from workshop control to the process planning module which allows generation of manufacturing alternatives for bottle neck resources which deviate from the optimal manufacturing routes with the least time and cost.

Real improvement of production control can only be achieved by integration of a computer-aided process planning system with a workshop scheduling system that fully utilises the benefits of manufacturing alternatives provided by non-linear process plans. Such a system will have to be merged into a decentralized production planning and control environment. The different production control activities in a decentralized and distributed system will have to be coordinated with respect to common production goals using adaptive control strategies. The integrated process planning and workshop scheduling information from a common relational data base could be used for a comprehensive evaluation of production using logistics and manufacturing costs criteria. Such an evaluation would provide the essential information that is required for aforesighted and rational planning of processes, production and facilities.

The above approach is followed in the new ESPRIT sponsored Project COMPLAN [66). The project objective is to develop an integrated system for concurrent process planning, scheduling and shop floor control based on non-linear process plans. The following modules will form the COMPLAN system (Figure 13):

Figure 13. ESPRIT Project 6805: COMPLAN Main Components of the System

(Wiendahl, H. P., [66])

A process planning oriented CAD/CAPP Programming Interface will provide the required direct coupling to a wide variety of CAD-systems and provide technical and geometric information. An existing semi-automatic process planning system (running in 40 companies) and an existing expert shell for automatic process planning of a limited workpiece spectrum (EP #2457) will be adapted and merged to form a single planning environment allowing the generation of non-linear process plans, It will be integrated with a graphical editor for non-linear process plans. A Process Plan Evaluator will allow the process planning module to consider both actual and forecasted workshop loading information during the generation of non-linear process

plans and during just-in-time process planning. Furthermore, it allows manufacturing alternatives to be assessed with respect to times, costs, and technical validity A Workshop Control System based on non-linear process plans will be integrated with the process planning system. A Production Evaluator will examine the quality of a schedule and determine past workshop performance. The evaluation results will support and control both process planning and scheduling.

7.1.3 Modular Integration

Thethirdapproach tointegrationcan beconsideredarealistic intermediate between the first two approaches [Q, 65, 771. This approach is essentially modular where process planning and production planning and control do not need to be one system. However, the CAPP and PPC systems need to have the ability to interact with the shop floor disturbances (events), non-linear process plans, and dynamic resources and constraints. In this approach, integration schemes and a separate module called the 'Integratot [67] were developed to bridge the functional and data gaps between CAPP and PPC. Physically, the database can be a common or a standard distributed database. However, common databaseentitiesdefinition, structures, interpretationsof eventsand synchronization issues in a multi-tasking, heterogeneous, networkedparallel environment are considered. The modular approach has practical advantages including flexibility of implementation as well as the possibility of integrating existing CAPP and PPC systems in use by any given company.

7.2 Dynamic Process Planning in a Reactive Environment

A dynamic and reactive computer aided process planning environment has been created. This system, called RPE (Reactive Planning Environment) was conceived and implemented [65] to achieve a number of objectives:

Represent process plans at various levels of detail and abstraction to suit both detailed (micro) process planning and operations (macro) planning and sequencing. Allow the combination and representation of mixed domain operations in a plan. In particular, it deals with product assembly planning as well as other processes which may be required to complete a product such as welding, soldering, cleaning, inspection, fabrication and machining at the macro operation level (not detailed task planning). Represent precedence constraints for a given task as well as the resources required for completing the task. These are used to decide on alternate plans as needed. Capture and model alternate resources, alternate routes and alternate processes, albeit less than optimal, along with the preferred or best plan. Represent the resources and plant by models compatible with those used by PPC systems. Allow alternate plans evaluation, according to user defined criteria such as time, scrap rate, load balancing and cost, and select the best plan under given conditions such as absence or over-utilization of certain resources.

A scheme for representing micro and macro tasks in a process plan and routing sheets using a multi-layered precedence graph has been developed. Resources are modelled and associated with each task. "PreConstraints" define order between macro task (operations). "AltConstraints" are used to specify alternative processing methods within a process plan which can achieve a common end result (figures 14 and 15). For example, alternate plans for a product assembly using manual, semi-automatic or fully automated systems may be represented andusadassubstitutes todeal with bottlenecks. These alternatives are examined and evaluated as needed, using graph search methods, in response to feedback from the PPC system. RPE uses a featureAased, object-oriented approach [60] to represent a product structure hierarchically. Bills of material produced by conventional CAD systems may also be used. This effectively links CAD with process planning. Current process planners produce detailed (micro) tasks in a single domain (e.g., machining or assembly). The resulting plansare input to RPE andcorresponding precedence graphs are generated. These are edited and modified interactively by the user to add operations not considered by the micro process planners. It is also possible to enter the whole plan and alternatives interactively by the user through an effective graphical user interface. The output from RPE is the plan recommended. The precedence graph is converted to the usual sequential processplanformatinaflatfileforuse bytraditional PPC

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w E 1 /! % ti- F 2

Legend

Note: One MicmTask within each MacroTask must be selected.

Figure 14. Process alternatives representation (non-linear plans) and relationship between macro and micro tasks

(EIMaraghy, H., 191)

Figure 15. Plant model including resources and tools (EIMaraghy, H. [9])

systems. The selected plan and operations sequence are also displayed along with the resources layout within the plant.

8.0 DISTRIBUTED PROCESS PLANNING

A trend is evolving for distributed and more decentralized process planning systems. These would be a collection of process planning systems, each with a limited function or scope and more specialized nature, which are loosely connected to form a "system of systems" with an overall supervisor which coordinates their interaction and the flow of control and data between them. These systems could reside on one or more computers. There are a number of factors which motivate this trend:

the recent research and developments in intelligent manufacturing systems and "holonic" manufacturing advocates the use of intelligent agents (both hardware and software) each with built-in planning, reasoning and replanning capabilities.

modem machining centres, workstations, robots, etc. have sophisticated controllers with powerful CPU, memory and programming abilities

Flexibility will increase by shifting detailed process planning tasks closer to the manufacturing process, i.e. to the machine itself. Thus autonomous islands could become more responsible for their process planning tasksand NC programming would be shifted to the machine controller with its built-in knowledge and procedures.

New decentralized organizational and management structures in factories and companies will give rise to new CAPP requirements. For instance process planning could be pe rformed on demand similar to the Kanban pull technique in production scheduling.

This trend toward distributed process planning would simplify both the development and use of process planning systems and improve response time and facilitate portability of planning knowledge.

9.0 PROCESS PLANNING FOR QUALITY

Decisions made in the course of process planning have a significant effect on the resulting product quality, in addition to the production time and cost. The selection of manufacturing technology, at the generic level, puts constraints on the surface quality or the geometric and dimensional variation to be achieved. Machines, tools and processes exhibit different levels of process capability. The choiceof a particular resource largely determines the ability of consistently meeting engineering requirements for tolerance, surface finish, fit or weld quality. Some methods and sequences selected in process planning may be more prone to errors and inconsistencies due to a large number of setups or improper choice of references.

In addition, the increased reliances on electronic documentation of both the product and process specifications presents a quality assurance challenge in terns of the traceability and assessment of all process changes during the manufacture of complex productsand adherence to the QA procedures as per IS0 9000 standards.

A close coupling between manufacturing process planning and inspection process planning will gene,rally contribute to the closure of the quality assurance loop and when taken in the wider context of concurrent engineering will ensure that quality is designebin from the start.

10.0 NON-TRADITIONAL PROCESS PLANNING APPLICATIONS

Traditionally, process planning focused more on metal removal operations (78-821. Applications in this domain are the most mature, although a great deal more work is still needed in the NC machining area. Some of the new developments in incress manufacturing and rapid prototyping [83] may change the nature of and the need for NC process planning for machining. As metals and strong composites are used in rapid prototyping processes for producing functional parts rather than prototypes, and as the economy and efficiency of these processes improves, their use in small and medium lot size production will increase and the need for metal removal process planning and related tasks may decrease, anddifferent typesofprocessplanningtosuitthe newprocesseswill be needed.

In the meantime, there is growing awareness of the need for efficient process planner sindomainsotherthan metal removal. The following is a brief description of some of these non-traditional process planning applications.

10.1 Assembly Process Planning

'The objective is to use the product model and attributes describing the connectivity and relationships between the various partsand subassemblies togenerate the bestassembly sequence, specify required fixtures and assembly tools, calculate assembly timeandcost and provide feedbacktodesigners regarding theease of assembly of the designed product (figure 16). Several assembly planning systems have been reported with varying degrees of automation and integration with design 184-94, 100, 109-1111.

10.2 Inspection Process Planning

The objective of tactile CMM inspection planning is to establish the best sequence of inspection steps, the detailed inspection procedure of each feature, features accessibility by the probes, probe path planning and collision checking, generating the inspection machine control program (e.g. through DMlS interface) andcalculating inspection time andcost(figure 17). In addition tothe inspection knowledgeand CMM related rules, information regarding geometry, tolerances and datums are needed as well as familiarity with tolerancing standards (such as ANSI Y14.5 M). Few systems have been reported in this area [95-971. Inspection planning also applies to optical inspection (figure 18) and printed circuit board inspection and testing.

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Air cylinder assembly.

cent- anachmnt - blocking---'

-/--- bearing-O-ring -m b.ri.

bearing pi sl o n - rod

piston-screw

piston-O-ring piston

M Y cover-screw

ww-o-ring cover mv.

Air cylinder graph model.

Figure 16. Assembly Planning of an Air Cylinder [89]

CAD W

k a u r u

INSPECTION FEATURE ANALYSIS

SuihbiTly lor CMiA dusluinp. Readnblity, h u m s .

TCi8MsU.

Inrp.ch hh Plnning. VWikaSm n d Dynamic

S h U k b l

Figure 17. Main Functions of a Tactile Inspection Planning System

10.3 Robots Task Planning

Task planning for robots may include several manufacturing processesdependingon the application in which robotsare used, be it assembly, welding, inspection, finishing, etc. In addition to the domainspecific processplanning, robotsrequireadditionalplanning for: 1)converting high level taskspecifications(e.g. assemble motor endcap and body) to optimally sequenced moves and actions, generating and planning a collision free motion path [101-103], planning grasping and work-holding strategies, synchronizing and coordinatingtheactionsofmorethanonerobot, error-recoveryand

'Figure 18. General Structure of Multi-Agent Planner and Execution Module [lo41

replanning, grasp planning and producing the robot control program in a robot language such as VAL II 1104-1081.

10.4 Work-holding and Fixture Planning

An important aspect of process planning which has been included in only a few CAPP systems is fixturing. Planning the work holding procedures, sequence and required hardware involves many considerations: i) geometric and technological infonation in the part model, ii) set-upand fixture planning. Theoverall procedure relating to set-up and fixture planning activities of a recently implemented system [14,15] is illustrated in figure 19

The overall objective in setup planning is to maximize the numberof operations that can be performed in a single setup orto minimize the total number of set-ups for all the operations required for a workpiece. It is also necessary to maximize the accuracy that can be achieved. Clustering features to be machined in one setup depends on the tool approach direction, tolerances, feature interaction and good machining practice. Fixture planning considers locating, supporting and clamping considerations, the selection of fixturing elements and their assembly.

The same principle used for fixture planning in metal removal also apply to work holding for other applications such as assembly where much more work is still needed.

10.5 Process Planning for Sheet Metal Working

Planning activities can involve the unfolding of 3-0 product shapes into flat pieces and the planning of folding steps nesting and cutting of pieces out of sheet metal and other material (e.g. routing, laser, waterjets, etc.), preparing the machine controlling steps and programs, planning of presses work including the selection of dies and punches and programming these machines.

10.6 Process Planning for Welding Operations

The planning activities use the product model data to plan the welding sequence or path(.+ track the seams, select the best tips and welding parameters, and generate programs to control the welding heads.

These are but a few examples of applications which serve to illustrate the richness and versatility of this field and indicate the need for more research and development efforts.

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3D CAD M&l

I

Stability analysis I

Figure 19. An overall procedure relatingset-upplanning and fixture planning activities ( Nee 11151).

11.0 DESIRABLE CHARACTERISTICS OF A CAPP SYSTEM

Assessment of the CAPP systems and technology todate, and the limited degree of proliferation and impact they had on industry todate suggest the following desirable characteristics of an effective CAPP system.

It should: be modular in order to incorporate some of the new trends such 'as generic, rapid, distributed andlor reactive planning. be transparent in order to facilitate the understanding of its structure, behaviour and outcome by its users. be extendable and adaptable to new applications and facilitate the inclusion of new data bases and knowledge, as well as being customizable. provide effective knowledge acquisition, representation and manipulation mechanisms as well as means to check the completeness and consistency of that knowledge.

* keep a human in the loop, to participate in some decision making, provide heuristics as needed and supplement the system's abilities.

interaction by facilitating inputs, producing outputs 6 reports in flexible formats and display the results graphically.

planning and control.

possible.

Provide an excellent user interface to support effective

be effectively integrated with both design and production

include as many of the emerging life cycle considerations.as

be easy to install and use, fast and invisible.

12.0 DISCUSSION AND CONCLUSION

CAPP is the application of computers to assist the human process planner in the process planning function. In its lowest form it will reduce the time and effort required to prepare process plans and provide more consistent process plans. In its most advanced state it will provide the the automated interface between CAD and CAM and in the process achieve the complete integration within the manufacturing system.

Good progress is being made in the automation of the actual production process and also the product design element However the interface between design and production presents the greatest difficulty in accomplishing integration. CAPP has the potential to achievethisintegration. Delphi forecastssuggestthatby 1995,50% of all process plans used to produce parts or assemblies will be computergenerated in companieswith fewerthan 1000 employees. Thus examining the trends in CAPP and those of CIM we can see that CAPP is now in a strategic position to the bridge between CAD and CAM and is a crucial area for research and development. To date only very few computer-aided production-planning systems have been used by industry with limited impact on manufacturing. This is due to the complexity of the planning domain, lack of scientifically rigorous foundation forplanning methodsand absence of true integration with design.

Key research issues in CAPP include: i) development of a complete product definition that captures the design as well functional and technological aspects of the product which are neededforprocess planing, ii) the understanding anddeveloprnent of those mapping rules and techniques for transforming design features and representations, iii) the development of and access to the necessary technological data and knowledge base, iv) improving and developing planning search and methodologies, v) achieving effective two-way communication and integration between CAPP and PPC, vi) further development of the scientific and technological foundations needed to extend CAPP to other application domains, and new frontiers, and vii) contribute to the ongoing standardization efforts which will impact process planning.

One challenge that CAPP researchers within ClRP are beginning to tackle is the problem of unification of technologies and definitions used in the field of manufacturing process planning and related activities.

Computer-Aided Process Planning will continue to receive significant attention from the industrialists and the academicians alike becauseof the strategicandimportantrole it playsin achieving a seamless integration between various manufacturing activities in a CIM environment.

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