ABSTRACT
Monitoring and diagnosis play an important role in modern manufacturing engineering. They help to detect product defects and process/system malfunctions early, and hence, eliminate costly consequences. They also help to diagnose the root causes of the problems in design and production and hence minimize production loss and at the same time improve product quality. In the past decades, many monitoring and diagnosis methods have been developed, among which the fuzzy set theory has demonstrated its effectiveness. This chapter describes how to use the fuzzy set theory for engineering monitoring and diagnosis. It introduces various methods such as fuzzy linear equation method, fuzzy C-mean method, fuzzy decision tree method, and a newly developed method, fuzzy transition probability method. By using good examples, it demonstrates step by step how the theory and the computation work. Two practical examples are also included to show the effectiveness of the fuzzy set theory.
