Abstract

This study aims to implement a Case-Based Reasoning (CBR) for diagnosis and recommendations for the maintenance and repair of machines in the Department of Mechanical Engineering Polman Negeri Bangka Belitung. The research begins with the process of collecting data for knowledge bases related to the maintenance and repair cases of these machines. Furthermore, the data is modeled based on its attributes. The cases that have been modeled are input into the CBR system by applying the similarity function of weighted sum and Euclidean distance. The higher the similarity between a new case and cases that have been stored on a case base, the more suitable the solution on a case base can be applied in other cases. The results obtained were 5 case bases, i.e. the base case of flat grinding machines, the case base of lathe machines, the case base of milling machines, the case base of CNC machines, and the case base of the welding machines. The results of the CBR system are able to diagnose the causes of problems with machines through the symptoms of problems that occur and able to provide recommendations for the maintenance and repair of these machines.

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