Multiobjective Multistate System Preventive Maintenance Model with Human Reliability
Modern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor ass...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/6623810 |
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| author | Chao-Hui Huang Chun-Ho Wang Guan-Liang Chen |
| author_facet | Chao-Hui Huang Chun-Ho Wang Guan-Liang Chen |
| author_sort | Chao-Hui Huang |
| collection | DOAJ |
| description | Modern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor associated with maintenance personnel—a condition-based multiobjective MSS preventive maintenance model (MSSPMM). The study assumes that no more than one maintenance activity is performed to achieve the most appropriate preventive maintenance (PM) strategy and easy implementation and to reduce maintenance error due to human reliability. The MSS performance based on mean system unavailability and total maintenance cost is evaluated using a stochastic model approach, and then, the MSSPMM is used for optimisation. A customised version of the nondominated sorting genetic algorithm III is employed to ensure efficient solution of the PM model with human reliability—which is considered a constrained multiobjective combinatorial optimisation problem. The optimised solutions are determined from the nondominated Pareto frontier comprising the diversified PM alternatives. A helicopter power transmission system is used as an example to illustrate the efficacy and applicability of the proposed approach through sensitivity analyses with relevant parameters. |
| format | Article |
| id | doaj-art-6bc97057cf374b8a81fe501ce5bf98b8 |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-6bc97057cf374b8a81fe501ce5bf98b82025-02-03T01:27:20ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742021-01-01202110.1155/2021/66238106623810Multiobjective Multistate System Preventive Maintenance Model with Human ReliabilityChao-Hui Huang0Chun-Ho Wang1Guan-Liang Chen2Department of Applied Science, R.O.C. Naval Academy, Kaohsiung 813205, TaiwanChung Cheng Institute of Technology, National Defense University, Taoyuan 335009, TaiwanChung Cheng Institute of Technology, National Defense University, Taoyuan 335009, TaiwanModern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor associated with maintenance personnel—a condition-based multiobjective MSS preventive maintenance model (MSSPMM). The study assumes that no more than one maintenance activity is performed to achieve the most appropriate preventive maintenance (PM) strategy and easy implementation and to reduce maintenance error due to human reliability. The MSS performance based on mean system unavailability and total maintenance cost is evaluated using a stochastic model approach, and then, the MSSPMM is used for optimisation. A customised version of the nondominated sorting genetic algorithm III is employed to ensure efficient solution of the PM model with human reliability—which is considered a constrained multiobjective combinatorial optimisation problem. The optimised solutions are determined from the nondominated Pareto frontier comprising the diversified PM alternatives. A helicopter power transmission system is used as an example to illustrate the efficacy and applicability of the proposed approach through sensitivity analyses with relevant parameters.http://dx.doi.org/10.1155/2021/6623810 |
| spellingShingle | Chao-Hui Huang Chun-Ho Wang Guan-Liang Chen Multiobjective Multistate System Preventive Maintenance Model with Human Reliability International Journal of Aerospace Engineering |
| title | Multiobjective Multistate System Preventive Maintenance Model with Human Reliability |
| title_full | Multiobjective Multistate System Preventive Maintenance Model with Human Reliability |
| title_fullStr | Multiobjective Multistate System Preventive Maintenance Model with Human Reliability |
| title_full_unstemmed | Multiobjective Multistate System Preventive Maintenance Model with Human Reliability |
| title_short | Multiobjective Multistate System Preventive Maintenance Model with Human Reliability |
| title_sort | multiobjective multistate system preventive maintenance model with human reliability |
| url | http://dx.doi.org/10.1155/2021/6623810 |
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