Title: Using data mining in the manufacturing systems for CAD model analysis and classification

Authors: Hisham Al-Mubaid, Emad S. Abouel Nasr, Ali K. Kamrani

Addresses: Department of Computer Science, University of Houston-Clear Lake, Houston, TX, USA. ' Department of Mechanical Engineering, Helwan University, Helwan, Cairo, Egypt. ' Department of Industrial Engineering, University of Houston, Houston, TX, USA

Abstract: The applications of data mining in engineering and manufacturing are enormous and useful for helping in the analysis of large data and information repositories for the discovery of trends, patterns and knowledge. In industrial engineering and manufacturing systems, the data may contain valuable information, or example, in downstream CAM applications such as Computer Aided Process Planning (CAPP). In this paper, we present a new approach for mining large quantities of machining features, Computer-Aided Design (CAD) models and manufacturing data. The approach is based on data mining and uses learning-logic classification techniques for mining 3D CAD data. The proposed approach was evaluated in CAD model analysis, specifically in classification tasks. The experimental results proved that the method is effective in terms of classification accuracy and can be used as an efficient data mining tool for CAD model analysis and classification.

Keywords: data mining; CAD models; CAD model classification; CAM; computer aided process planning; CAPP; feature analysis; computer aided design; computer aided manufacturing; machining features; CAD model analysis.

DOI: 10.1504/IJASM.2008.019604

International Journal of Agile Systems and Management, 2008 Vol.3 No.1/2, pp.147 - 162

Published online: 17 Jul 2008 *

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