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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/505

Title: Automatic classification of CAD models
Authors: Ip, Cheuk Yiu
Keywords: Computer science;Computer-aided design;Machine learning
Issue Date: 3-Aug-2005
Abstract: Classification of CAD helps the reuse of engineering designs and accelerates product development. Existing research, based on either group technology or fixed modeling matching algorithms, impose a priori categorization schemas on engineering data or require significant human labeling. This research introduces a framework for automatic classification of CAD models using a pattern classification model. It separates feature extraction and classification from 3D shape matching procedures. Different shape features and classifiers can be incorporated to fit example CAD/CAM oriented classification schemas. Two example approaches are presented to demonstrate how CAD models can be classified with supervised machine learning. The first approach describes how to perform nearest neighbor shape classification with multiple descriptors using a weighting formulation. Appropriate weights of different shape descriptors are estimated through training. The second approach aims at classifying prismatic-machined, and cast-then-machined artifacts. These manufacturing processes are discrimated by normal surface curvature and nonlinear support vector machines.
URI: http://hdl.handle.net/1860/505
Appears in Collections:Drexel Theses and Dissertations

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