Multiobjective Multistate System Preventive Maintenance Model with Human Reliability
Autor: | Chun-Ho Wang, Chao-Hui Huang, Guan-Liang Chen |
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Rok vydání: | 2021 |
Předmět: |
0209 industrial biotechnology
Power transmission Article Subject Stochastic modelling Computer science 020209 energy Sorting Pareto principle Aerospace Engineering TL1-4050 02 engineering and technology Preventive maintenance Reliability engineering 020901 industrial engineering & automation Genetic algorithm 0202 electrical engineering electronic engineering information engineering Unavailability Motor vehicles. Aeronautics. Astronautics Human reliability |
Zdroj: | International Journal of Aerospace Engineering, Vol 2021 (2021) |
ISSN: | 1687-5974 1687-5966 |
Popis: | 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. |
Databáze: | OpenAIRE |
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