Intelligent Fault Diagnosis System for Enhancing Reliability of Coil-Spring Manufacturing Process
(주)코리아스칼라
- 최초 등록일
- 2016.04.02
- 최종 저작일
- 2004.09
- 11페이지/ 어도비 PDF
- 가격 4,200원
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서지정보
ㆍ발행기관 : 대한안전경영과학회
ㆍ수록지정보 : 대한안전경영과학회지 / 6권 / 3호
ㆍ저자명 : 허준, 백준걸, 이홍철
영어 초록
The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.
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