基于聚合算法的失效相关多部件系统维修策略优化
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摘要
针对多部件系统维修策略优化问题,在考虑失效相关和经济相关的基础上,从建模和求解算法两方面展开了研究。建立了多部件系统折扣准则模型,得到了维修费率的最优方程,并转化为线性规划问题。采用聚合算法减小线性规划问题的规模,并利用迭代算法求得其最优解。最后通过数值算例,说明了失效相关程度对折扣总成本以及最优维修策略的影响,探究了模型中成本参数对维修策略的影响。算法对比的实验结果显示,采用聚合迭代算法可以有效提高运算速度,降低内存占用。
Aiming at the optimization of a maintenance strategy for multi-component systems,modeling methods and algorithms are studied based on failure and economic interactions.The model of discount criterion for multi-component systems is established.The optimal equation of maintenance cost is obtained and transformed into a linear programming problem.The aggregation algorithm is applied to reduce the scale of the linear programming problem and the iterative algorithm is applied to get optimal solutions.Finally,the influence that the degree of failure exerts on the total cost of the discount and the optimal maintenance strategy are illustrated by numerical cases.The influence of the cost parameters on the maintenance strategy is discussed.Experimental results show that the iterative algorithm effectively improves computing speed and reduces memory consumption.
Aiming at the optimization of a maintenance strategy for multi-component systems,modeling methods and algorithms are studied based on failure and economic interactions.The model of discount criterion for multi-component systems is established.The optimal equation of maintenance cost is obtained and transformed into a linear programming problem.The aggregation algorithm is applied to reduce the scale of the linear programming problem and the iterative algorithm is applied to get optimal solutions.Finally,the influence that the degree of failure exerts on the total cost of the discount and the optimal maintenance strategy are illustrated by numerical cases.The influence of the cost parameters on the maintenance strategy is discussed.Experimental results show that the iterative algorithm effectively improves computing speed and reduces memory consumption.
引文
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[2]HEPING L,ESTELLE D,LAURENCE D.A condition-based maintenance policy for multi-component systems with Lévy copulas dependence[J].Reliability Engineering and System Safety,2016,149(1):44-55.
[3]TOMASZ N,SYLWIA W.On problems of multi-component system maintenance modeling[J].International Journal of Automation and Computing,2009,6(4):364-378.
[4]CHAN J,SHAW L.Modeling repairable systems with failure rates that depend on age and maintenance[J].IEEE Trans.on Reliability,1993,42(4):566-571.
[5]WANG H,PHAM H.Some maintenance models and availability with imperfect maintenance in production systems[J].Annals of Operations Research,1999,91(1):305-318.
[6]HONG H P,ZHOU W,ZHANG S,et al.Optimal conditionbased maintenance decisions for systems with dependent stochastic degradation of components[J].Reliability Engineering and System Safety,2014,121(1):276-288.
[7]GOLMAKANI H R,MOAKEDI H.Periodic inspection optimization model for a two-component repairable system with failure interaction[J].Computers&Industrial Engineering,2012,63(3):540-545.
[8]HUYNH K T,BARROS A,BERENGUER C.Multi-level decisionmaking for the predictive maintenance of k-out-of-n:F deteriorating systems[J].IEEE Trans.on Reliability,2015,64(1):94-117.
[9]CANH V H,DO P,BARROS A,et al.Maintenance grouping strategy for multi-component systems with dynamic contexts[J].Reliability Engineering and System Safety,2014,132(132):233-249.
[10]姚运志,孟晨,王成.考虑失效相关的多部件系统最优预防维修策略[J].计算机集成制造系统,2013,19(12):2976-2981.YAO Y Z,MENG C,WANG C.Optimal preventive maintenance policies for a multi-unit system considering failure interactions[J].The International Journal of Advanced Manufacturing Technology,2013,19(12):2976-2981.
[11]张卓琦,吴甦,李斌锋.考虑故障相关的两部件系统机会维修策略[J].清华大学学报(自然科学版),2012,52(1):122-127.ZHANG Z Q,WU S,LI B F.Opportunistic maintenance policy for a two-unit system with failure interactions[J].Journal of Tsinghua University(Science and Technology),2012,52(1):122-127.
[12]杨元,黎放,侯重远,等.基于相关性的多部件系统机会成组维修优化[J].计算机集成制造系统,2012,18(4):827-832.YANG Y,LI F,HOU C Y,et al.Opportunistic group maintenance optimization of multi-unit system under dependence[J].The International Journal of Advanced Manufacturing Technology,2012,18(4):827-832.