Fault diagnosis of electronic system using artificial intelligence

With increasing system complexity, shorter product life cycles, lower production costs, and changing technologies, the need for intelligent tools for all stages of a product's lifecycle is becoming increasingly important. The purpose of this article is to give a brief review how AI has been used in the field of electronic fault diagnosis. Topics discussed include: rule-based diagnostic systems; model-based diagnostic systems; case-based reasoning (CBR); fuzzy reasoning and artificial neural networks (ANN); hybrid approaches; IEEE diagnostic standards and automated diagnostic tool future developments.