A Web-Based Intelligent Hybrid System for Fault Diagnosis

AI in Equipment Maintenance and Support

Volume

Papers from the 1999 AAAI Spring Symposium

Contents

In traditional help desk service centres, service engineers provide a world-wide customer support service through the use of long-distance telephone calls. Such a mode of support is found to be inefficient, ineffective and generally results in high costs, long service cycles, and poor quality of service. With the advent of Internet technology, it is possible to deliver customer service support over the World Wide Web. This paper describes a Web-based intelligent fault diagnosis system, known as WebService, to support customer service over the Web. In the WebService system, a hybrid case-based reasoning (CBR), artificial neural network (ANN) and rule-based reasoning (RBR) approach is adopted for machine fault diagnosis. In this approach, ANN and RBR are incorporated into the CBR cycle (i.e. Retrieve, Reuse, Revise and Retain) instead of using traditional CBR technique for indexing, retrieval and adaptation. The hybrid approach has been implemented to provide efficient online intelligent machine fault diagnosis over the World Wide Web.