Indexing and retrieval in case-based process planning for multi-stage non-axisymmetric deep drawing |
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Authors: | W.Y. Zhang S.B. Tor G.A. Britton |
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Affiliation: | (1) Institute of Artificial Intelligence, Zhejiang University, Hangzhou, 310027, China;(2) Cad/Cam Lab, School of Mechanical and Production Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798 Singapore |
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Abstract: | This paper presents a case-based reasoning (CBR) methodology for computer-aided process planning (CAPP) for multi-stage, non-axisymmetric sheet metal deep drawing. The methodology addresses the indexing and retrieval of process planning cases. Planning cases are indexed via a feature-based representation of deep drawn parts. Efficient case retrieval is achieved by a feature-based similarity analysis between a new deep drawn part and existing parts in the case library. An illustrative example is included to demonstrate the operation of the proposed approach and show its effectiveness in speeding up CAPP for multi-stage non-axisymmetric deep drawing. This revised version was published online in April 2005 with a correction to the corresponding author’s address. |
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Keywords: | Case-based reasoning Deep drawing Feature-based representation Process planning |
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