| Summary: | 碩士 === 國立臺北科技大學 === 機電整合研究所 === 89 === In order to predict a potential fault that might be about to occur, and to understand what causes the fault of manufacturing equipment, the strategy of predictive maintenance is very important. Taking semi-conductor equipment as an example, for the purpose of sustaining the overall performance, the strategy should be aimed to instantly provide the conditions of equipment in order to prevent any errors during the manufacturing process, and to immediately provide the related information and diagnosis as the guidelines for regular maintenance as well as preventive maintenance.
To realize the strategy as mentioned, this paper applies the well-known dynamic simulation software-ADAMS to develop a virtual equipment platform to generate fault warning-mode through virtual prototyping instruments. This virtual equipment platform can generate predictable fault symptoms. Therefore, the main purpose of this virtual equipment is to develop a predictable fault mode for the real machine, and then to proceed diagnosis reasoning in order to determine what causes failure. The advantage of developing virtual equipment is to generate parametric faults instead of intentionally making destructive faults in the real machines. It leads to clearly relate the causes and the characteristics of faults. Therefore, it becomes very easy to identify the faults. In other words, the main purpose of this study is to apply CAE to assist the fault diagnosis in order to reduce the maintenance problems for the equipments in operating. This study has also taken a rotor system, spur gear pair and a die-attaching machine as examples to verify the feasibility of this virtual-equipment diagnosis platform, and establish a fault reconstruction simulator to simulate the condition when a fault occurs.
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