標題: | A neural network approach to the classification of 3D prismatic parts |
作者: | Wu, MC Jen, SR 交大名義發表 工業工程與管理學系 National Chiao Tung University Department of Industrial Engineering and Management |
關鍵字: | classification;group technology;neural network;prismatic parts;rectilinear;skeleton |
公開日期: | 1996 |
摘要: | This paper presents a neural network approach to the classification of 3D prismatic parts based on their global shape information modelling. In this approach, a 3D part is modelled by the contours of its three projected views, which are approximately represented by three rectilinear polygons. The global shape information of each polygon is modelled by its simplified skeleton, which originally is of a tree structure and can be represented by several vectors by a conversion method. These vectors are the input to a polygon classifier which is constructed on the basis of the back-propagation neural network model. The classification results of polygons can be used to group the 3D prismatic parts into families in a hierarchical manner, by setting different levels of similarity criteria. The proposed method for classifying 3D workpieces can be used to enhance the productivity of design and manufacturing processes. By retrieving and reviewing similar parts from the part families, the designers or process planners could be greatly assisted in performing a new task. That is, they can avoid the reinvention of an existing design and can create a new design by modifying existing ones. |
URI: | http://hdl.handle.net/11536/1560 |
ISSN: | 0268-3768 |
期刊: | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY |
Volume: | 11 |
Issue: | 5 |
起始頁: | 325 |
結束頁: | 335 |
顯示於類別: | 期刊論文 |