ABSTRACT
This chapter aims to improve the computerizing of failure detection, testing, and maintenance, artificial intelligence and knowledge based techniques. An expert system essentially consists of a knowledge base containing facts, rules, heuristics, and procedural knowledge, and an inference engine which consists of reasoning or problem solving strategies on how to use knowledge to make decisions. Failure detection, testing, and maintenance are knowledge intensive and experience-based tasks. Several knowledge-based systems (KBS) exist that address some of the problems relevant to the detection/test/diagnosis/maintenance task. The failure detection/testing/maintenance KBS is implemented on a processor to assist the reasoning process of maintenance personnel or test equipment. For large KBS consisting of several knowledge bases nodes, the issues of control and communication are interrelated. The inference engine uses knowledge in the knowledge base to solve a specific problem by emulating the reasoning process of a human expert.
