Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes
碩士 === 國立成功大學 === 工業與資訊管理學系 === 104 === This study investigates the effects that the degree of the total degradation has on the occurrence frequency of random shocks based on the multiple dependent competing failure processes (MDCFP) to obtain the optimal preventive maintenance strategy. Research on...
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ndltd-TW-104NCKU50410812017-10-29T04:35:10Z http://ndltd.ncl.edu.tw/handle/33756539819257851539 Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes 相依多重競爭失效模式之維護成本分析 Bing-JianLi 李秉鍵 碩士 國立成功大學 工業與資訊管理學系 104 This study investigates the effects that the degree of the total degradation has on the occurrence frequency of random shocks based on the multiple dependent competing failure processes (MDCFP) to obtain the optimal preventive maintenance strategy. Research on preventive maintenance and multiple failure modes mostly assumed that the occurrence frequency of random shocks is independent of the degree of degradation. However, such an assumption is not practical in reality. This study uses a simulation method to generate the failure times and then adopts the generated failure times to obtain the optimal periodical inspection and preventive maintenance strategies. We also perform a sensitivity analysis by using the data of a micro-electro-mechanical system. The obtained results indicate that regarding to the periodical inspection, the low occurrence frequency of random shocks and inspection cost can effectively decrease the long-run maintenance cost. Moreover, with regard to the periodical preventive maintenance, the high soft failure threshold, low occurrence frequency of random shocks, and replacement cost can effectively reduce the long-run maintenance cost. Shiow-Yun Chang 張秀雲 2016 學位論文 ; thesis 61 zh-TW |
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碩士 === 國立成功大學 === 工業與資訊管理學系 === 104 === This study investigates the effects that the degree of the total degradation has on the occurrence frequency of random shocks based on the multiple dependent competing failure processes (MDCFP) to obtain the optimal preventive maintenance strategy. Research on preventive maintenance and multiple failure modes mostly assumed that the occurrence frequency of random shocks is independent of the degree of degradation. However, such an assumption is not practical in reality. This study uses a simulation method to generate the failure times and then adopts the generated failure times to obtain the optimal periodical inspection and preventive maintenance strategies. We also perform a sensitivity analysis by using the data of a micro-electro-mechanical system. The obtained results indicate that regarding to the periodical inspection, the low occurrence frequency of random shocks and inspection cost can effectively decrease the long-run maintenance cost. Moreover, with regard to the periodical preventive maintenance, the high soft failure threshold, low occurrence frequency of random shocks, and replacement cost can effectively reduce the long-run maintenance cost.
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Shiow-Yun Chang |
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Shiow-Yun Chang Bing-JianLi 李秉鍵 |
author |
Bing-JianLi 李秉鍵 |
spellingShingle |
Bing-JianLi 李秉鍵 Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes |
author_sort |
Bing-JianLi |
title |
Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes |
title_short |
Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes |
title_full |
Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes |
title_fullStr |
Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes |
title_full_unstemmed |
Maintenance Cost Analysis for Systems Subject to Multiple Dependent Competing Failure Processes |
title_sort |
maintenance cost analysis for systems subject to multiple dependent competing failure processes |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/33756539819257851539 |
work_keys_str_mv |
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