We describe a hybrid feature recognition method for machining features that integrates three distinct feature recognition methods: graph matching, cell-based maximal volume decomposition, and negative feature decomposition using convex decomposition. Each of these methods has strengths and limitatio
Knowledge-based feature recognizer for machining
β Scribed by Shee-Hock Yeo
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 711 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0951-5240
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β¦ Synopsis
Various methods of input format to manufacturing systems have been proposed. For an integrated manufacturing system, direct CAD data input is the most appropriate input format. Currently, the identification of general machinable features is limited in scope, The application of many feature recognition systems has not yet been tested thoroughly enough to verify their suitability for manufacturing activities, therefore a suitable feature recognizer is required, A software tool, GoldWorks III TM has been used to develop a knowledge-based feature modeller for machining. A frame-based approach to formulate a lattice structure of machining features is used to represent rotationally symmteric components.
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