| Summary: | 碩士 === 逢甲大學 === 工業工程與系統管理學研究所(工業工程學所) === 93 === In the age of knowledge economy, the industry's knowledge has become the most important asset of enterprise. How to keep the industry's knowledge and the staff experiences is the most important issue in the twenty-first century. In according to the failure characteristics of training simulator, a mixed failure diagnosis expert system, which consists of rule-based and case-based inference engines, has been developed to promote the efficiency of diagnosis in this study. In the case-based inference engine, the characteristic indices are used to classify the failure phenomena, firstly. The Analytic Hierarchy Process is then applied to determine the weight of characteristic indices. In the last stage, the grey relational analytic is used to calculate the similarities of reference cases. After verification, the corresponding calculation time is reduced by 81% comparing to conventional case-based inference engine. And the accuracy is up to 76.9%.
In order to evaluate the complete benefits of using on-line failure diagnosis and repairing system, a methodology is proposed in this study. The Balanced Scorecard is used to analysis the cause-and-effect relationships of maintenance strategy Four evaluation perspectives: knowledge accumulation, maintenance procedure, customer satisfaction and maintenance cost have been developed. Therefore the model of effectiveness evaluation is created. The results will become the modify basis of maintenance strategy.
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