Computer-Aided Process Planning
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Computer-Aided Process Planning Hoda ElMaraghy1 and Aydin Nassehi2 1 Intelligent Manufacturing Systems Center, University of Windsor, Windsor, ON, Canada 2 Department of Mechanical Engineering, University of Bristol, Bristol, UK
Synonyms CAPP
Definition Process planning, in the manufacturing context, is the determination of processes and resources needed for completing any of the manufacturing processes required for converting raw materials into a final product to satisfy the design requirements and intent and respect the geometric and technological constraints. Process planning is the link between product design and manufacturing (Scallan 2003). At the “macrolevel,” the sequence of operations and the selection of appropriate resources are the main concerns, whereas at the “micro” process planning level, the focus is on defining parameters of each operation, determining the time it takes to perform that operation, and selecting tools and fixtures as needed (ElMaraghy 1993). Computer-aided process planning (CAPP)
is the application of computer software to assist in these activities.
Theory and Application Theory and Methodologies Process planning techniques can also be classified into variant and generative. Variant (retrievalbased) process planning techniques that rely on a master template of a composite part are predicated on a predefined part/part family with some commonality in geometry or manufacturing processing. Upon retrieving a similar part, by visual inspection or using a coding and classification system, modifications are made to the process plan to suit the new part and its features. However, while this approach is fast, it results in less than optimal process plans. Generative process planning generates process plans from scratch for each part using rule- and knowledge-based systems, heuristics, and problem-specific algorithms. It requires full understanding and mathematical models of the processes and sufficient knowledge about its behavior, influencing factors, and constraints. Therefore, truly generative systems are not yet a reality with few exceptions and hybrid/ semi-generative approaches have been developed (Azab and ElMaraghy 2007a). Computerized process planning involves mathematical formulation of an optimization problem which seeks to minimize some cost function such as total process time and maximize resources utilization subject to
# CIRP 2016 The International Academy for Production Engineering et al. (eds.), CIRP Encyclopedia of Production Engineering, DOI 10.1007/978-3-642-35950-7_6551-4
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several technological constraints, the most important of which are the precedence constraints. Such models aim to establish the best operation sequence and resources required for each at the macrolevel or the specific values of operations parameters at the detailed microlevel. The challenges include knowledge representation schemes, heuristics, and optimization algorithms such as classical optimization algorithms, the traveling salesperson formulation and solution, precedence representation using graph, n
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