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Neural network based non-standard feature recognition to integrate CAD and CAM

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Öztürk, Nursel
Öztürk, Ferruh

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Elsevier

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In this paper, a neural network based feature recognition approach which is capable of extracting information from design database is proposed to automate the integration of the design and applications following design. CAD data base is converted to feature based model information which can be used by CAM applications. Multilayer perceptron neural network is provided with Boundary representation (B-rep) information to recognise simple and complex features. B-rep structure is used to process the face-score values in terms of geometry and topology of the solid model. The effectiveness of proposed approach is demonstrated with experimental results which show the validity of this method to recognise complex shape features.

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Feature recognitionneural networks, Feature-based design, Neural networks, Cad/cam, Manufacturing features, Discriminant-analyis, Automatic extraction, Components, Models, Decomposition, Heuristics, Systems, Computer aided design, Computer aided manufacturing, Data acquisition, Data structures, Database systems, Nonstandard feature recognition, Feature extraction

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Öztürk, N. ve Öztürk, F. (2001). "Neural network based non-standard feature recognition to integrate CAD and CAM" Computers in Industry, 45(2),123-135.

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