Abstract
Process planning determines how a product is to be manufactured and, therefore, is one of the key elements in the manufacturing process. The basic crux of computer-aided process planning (CAPP), however, is the diversity of manufacturing background and the complexity of process planning. Since the process plans are generated on demand with the manufacturing resources on a shop floor, modeling method of the manufacturing resources is one of most important issues in computer-aided process planning. Hence, the major objective of this research is to create a clustering-based modeling scheme of the manufacturing resources for process planning. This modeling scheme combines clustering method with averaging method so as to reasonably partition and classify the manufacturing resources on a shop floor. The proposed approach provides one of search strategies of machine tools for process planning, especially for the selection of machine tools. Finally, an illustrative example is applied to describe the clustering-based modeling scheme.
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