Title :
Expert system for tool wear monitoring in blanking
Author :
Mardapittas, A.S. ; Au, Y.H.J.
Author_Institution :
Dept. of Manuf. & Eng. Syst., Brunel Univ., Uxbridge, UK
Abstract :
A description is given of a simple yet powerful expert system created using the CRYSTAL shell which is able to monitor the potential and functional failures of the tool and the monitoring equipment. The techniques of feature extraction, selection and classification using the Bayesian rule are presented. Finally supervised learning, necessary when new situations are encountered, is also discussed
Keywords :
computerised monitoring; computerised pattern recognition; expert systems; learning systems; machine tools; manufacturing data processing; mechanical engineering computing; Bayesian rule; CRYSTAL shell; blanking; classification; feature extraction; functional failures; monitoring equipment; powerful expert system; supervised learning; tool wear monitoring;
Conference_Titel :
Intelligent Fault Diagnosis - Part 1: Classification-Based Techniques, IEE Colloquium on
Conference_Location :
London
