한국경영과학회:학술대회논문집 (Proceedings of the Korean Operations and Management Science Society Conference)
- 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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- Pages.960-968
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- 2005
하이브리드 데이터마이닝을 이용한 지능형 이상 진단 시스템
Intelligent Fault Diagnosis System Using Hybrid Data Mining
초록
The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.
키워드