توسعه سیستم پشتیبانی برنامه ریزی عملیات عمومی به کمک کامپیوتر
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|27209||2003||8 صفحه PDF||سفارش دهید||5071 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Materials Processing Technology, Volume 139, Issues 1–3, 20 August 2003, Pages 394–401
Although there is significant industrial need for comprehensive computer-aided process planning (CAPP) systems, most traditional CAPP solutions have been fragmented in nature. This is because each CAPP domain (assembly, machining, inspection, etc.) has been treated independently. This paper argues in favor of adopting ‘feature-orientation’ as the unifying theme and describes a Generic CAPP Support System along with the geometric feature recognition algorithms involved. Finally, some case studies derived from diverse application domains are presented to illustrate the advantages provided by the approach.
Computer-aided process planning (CAPP) has long been recognized to be an important component and enabler of Concurrent Engineering (CE). CE is facilitated by the availability of a computerized system for estimating production costs and times that, necessarily, includes a comprehensive and robust CAPP system. An effective CAPP system needs to be comprehensive because the production of a product (and, even, a single part) often needs a large variety of processes. Each of these processes may be a potential participant in the production process. These have to be individually evaluated in the context of the particular design specification of the part/product under consideration. A major hurdle faced by developers of a comprehensive CAPP system is that the processes it has to address have usually very little in common. The nature of each process and, hence, the knowledge base needed in its evaluation and design are quite distinct. As a result, the very subject area of CAPP has tended to be highly fragmented where each process domain is tackled in an independent and parallel fashion (see Fig. 1). Often, the resulting overall system is quite restricted in its scope and, even within this limited scope, there is considerable redundancy. In short, very little progress has so far been made with respect to meta-reasoning concerning the basic nature of process planning itself in terms data utilization and data processing methods so that one could hope to develop a comprehensive but more coherent and less redundant CAPP system. The present paper offers a solution that goes some way towards redressing this situation. Full-size image (9 K) Fig. 1. Traditional approach to the development of a comprehensive CAPP. Figure options The proposed strategy is based on the following premise. The creation of any domain-specific process plan typically involves two interacting thought processes: extracting relevant high-level information from the part/product needs to be collected, and reasoning over it on the basis of the corresponding domain-specific knowledge bases (DSKBs). Of these, the latter are likely to have very little in common. Hence the concept of DSKB cannot be the key to the desired ‘seamless’ integration of CAPP. In contrast, every CAPP sub-module involves reasoning over the part/product specification (specifications of form, dimensions, tolerances, surface roughness, etc.). Hence, if one wishes to develop a CAPP strategy that is applicable to (almost) every domain-specific CAPP sub-system, the strategy used must recognize and exploit part/product information as the unifying theme. An implication of the premise described above is that there could be a common ‘front end’ to every domain-specific CAPP sub-module that: (i) requires only the specification of the part/product as its input; and (ii) does not address issues requiring the use of a DSKB. We will refer to this ‘front end’ as the Generic CAPP Support System (GCAPPSS). This support system can be expected to act as the common starting platform for diverse domain-specific CAPP systems to be developed subsequently—thus reducing the overall effort needed in achieving a comprehensive CAPP system. The principal intent of the present paper is to argue in favor of the desirability, feasibility and utility of the concept of GCAPPSS. The rest of the paper is structured as follows. Firstly, arguments will be presented in favor of separating technological feature recognition (TFR)—a process implicit in any domain-specific CAPP—from geometric feature recognition (GFR) and making the latter as the ‘front end’ of GCAPPSS. Next, certain complexities associated with technological as well as GFR will be highlighted. This will be followed by a brief introduction of several GFR related algorithms developed by the authors. These algorithms are not only capable of extracting and recognizing geometric features, but also decomposing complex features into simpler ones to facilitate the identification of all possible feature relationships. The information so gathered is then reorganized to yield a multi-layered part representation that facilitates multiple interpretations of the same part from different CAPP viewpoints. Finally, the implications of GCAPPSS with respect to downstream TFR and CAPP processes will be highlighted.
نتیجه گیری انگلیسی
A major hurdle facing the development of a comprehensive CAPP system is that each CAPP domain is quite unique in terms of the analytical models and knowledge bases it utilizes. As a result, the field of CAPP has become highly fragmented. A unifying theme is needed to reverse this trend. One way of achieving this goal is to adopt the paradigm of feature-orientation as the unifying theme. This paper has explored one method of implementing this paradigm. The method involves the creation of a GCAPPSS that acts as the ‘front end’ for all domain-specific CAPP systems. The presence of such a ‘front end’ is helpful in avoiding unnecessary downstream redundancies. GCAPPSS itself consists of a generic geometric feature recognizer, an FRI, and a GOI. The first unit invokes a powerful set of algorithms that enable feature extraction, recognition, coding, classification and decomposition. The output from this system enables a multi-layered hierarchical part representation that seems to facilitate the interpretation of feature relations and the object itself. The system facilitates downstream TFR and CAPP exercises irrespective of the process domain. The paradigm of feature-orientation deserves further research. In particular, its effects on the knowledge structures used downstream need to be examined. Initial efforts in this direction have indicated that there exists a natural synergy between the paradigm of feature-orientation and CBR.