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Optimal System Design and Sequential Preventive Maintenance Under Uncertain Aperiodic-Changing Stresses

机译:不确定的非周期性变化应力下的最优系统设计和顺序预防性维护

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This paper presents a two-stage stochastic programming model with recourse for integrating the design and sequential preventive maintenance schedule of a system, which is subject to uncertain aperiodic-changing future usage stresses. Specifically, the usage stresses change as the system operates and preventive maintenance is conducted. The system undergoes imperfect repair according to the sequential preventive maintenance policy and minimal repair in response to emergency failures. The system is replaced when the maintenance is uneconomical due to the deterioration of the components. Under such future usage stresses and maintenance, this paper formulates the failure rates and lifetime distributions of components and the system, the failure rates increase with the usage stresses, and both the failure rates and usage stresses have an instantaneous incremental decrease at each preventive maintenance action. In the two-stage stochastic optimization model, the first-stage decision variables are the numbers of components to be used in the subsystems, and these variables affect the second-stage variables, which define the number of imperfect preventive maintenance actions before the replacement of the system and the aperiodic preventive maintenance time intervals for various future usage scenarios. Analytical properties about the failure rates of components and subsystems and the solution for minimizing expected system maintenance cost rate are derived. A decomposition method for solving the proposed two-stage stochastic model is designed based on the analytical results. Numerical examples and sensitivity analysis are provided for deep understanding of the proposed method.
机译:本文提出了一种具有资源的两阶段随机规划模型,用于集成系统的设计和顺序预防性维护计划,该模型受不确定的非周期性变化的未来使用压力的影响。具体来说,使用压力随着系统的运行和预防性维护而变化。该系统根据顺序预防性维护策略进行了不完善的维修,并针对紧急故障进行了最少的维修。当由于组件损坏而导致维护不经济时,请更换系统。在这种未来使用压力和维护的情况下,本文制定了组件和系统的故障率和寿命分布,故障率随着使用压力的增加而增加,并且在每次预防性维护措施下,故障率和使用压力都会瞬时增加。 。在两阶段随机优化模型中,第一阶段决策变量是子系统中要使用的组件数量,这些变量会影响第二阶段变量,第二阶段变量定义了在更换新组件之前不完善的预防性维护措施的数量。系统和各种未来使用场景的非定期预防性维护时间间隔。推导了有关组件和子系统的故障率的分析属性,以及用于最小化预期系统维护成本率的解决方案。根据分析结果,设计了一种求解所提出的两阶段随机模型的分解方法。数值算例和灵敏度分析为深入理解该方法提供了依据。

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