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

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...

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Bibliographic Details
Published in:Computers in industry 2001-06, Vol.45 (2), p.123-135
Main Authors: Ozturk, Nursel, Ozturk, Ferruh
Format: Article
Language:English
Subjects:
Automation
CAD
CAD/CAM
CAM
Computer aided design
Computer aided manufacturing
Feature recognition
Geometry
Integration
Neural networks
Recognition
Studies
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Summary: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.
ISSN:0166-3615
1872-6194
DOI:10.1016/S0166-3615(01)00090-2