A diagnosis scheme for a large-scale system

This paper presents a method for diagnosis in a large-scale system environment. The method utilizes the theory of hierarchical systems and hybrid diagnostic reasoning from AI (artificial intelligence). In shallow reasoning, which is a part of hybrid reasoning, the concept of entropy is used to determine which component (that might be responsible for a symptom observed) is to be tested next. The procedure is illustrated using a simulated example of a CIM (computer-integrated manufacturing) system, and is implemented on IntelliCorp's knowledge engineering environment (KEE).