Paper Details: Downloads: 911
Serial Number: P1121052399
Title: Intelligent automatic cutting-tool selections for turning operations
Authors: J. Balic and F. Cus and B. Vaupotic
Abstract: This paper introduces an intelligent system for selecting the best set of tools on the basis of a 3D CAD model and other relevant selection factors. An artificial intelligence method has been used for solving complex classification problems such as neural networks, trying to simulate and/or reach parallel information processing as used by the human brain when thinking of, remembering, or solving problems. On the basis of the knowledge acquired during this process of learning to search for cutting tools, the system responds to new unknown examples in the manner nearest to the experience acquired during learning. This concept was tried for the most widespread cutting process i.e. turning and the results reached are in conformity with expectations. A high-degree of classification was reached. The constant increase in knowledge that the system takes from its growing data base is considered to be a significant benefit of the proposed system. It is also suitable for classifying the cutting tools of other cutting processes due to its robustness and universality. The resulting solutions are comparable with the solutions given by experts. The system can be more practically used with minor corrections adapted to the user.
Keywords: Cutting tools, Intelligent automatic selection, Intelligent systems, 3D CAD model, Neural networks
Journal/Conference: ICGST Conference on Artificial Intelligence and Machine Learning, AIML-11
Volume:
Issue:
Submission Date: 12/24/2010 12:00:00 AM
Review Date: 3/12/2011 12:00:00 AM
Publishing Date: 4/6/2011 12:00:00 AM
Article Downloads: 911
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