Automated Inspection of Measurable Parts through the Use of Fuzzy Inductive Learning

摘要

Automated inspection in manufacturing industries is beginning to receive increased research attention in an attempt to separate defective parts from good ones in a fast and accurate manner. In order to better solve the problem mentioned above, an efficient fuzzy inductive learning method is addressed and implemented in this paper. By inducing fuzzy reasoning rules from numerical data, some criteria can be obtained and then be used to identify the defects of a measurable part.