基于故障预测的备件订购决策优化模型

摘要

Aiming at spare parts ordering problem for the key equipment system which degradation state distribution function is unknown , a kind of spare parts order decision optimization method which considered withcombining offailure prediction results and spare parts ordering was presented based on failure prediction .Firstly, according to the remaining life prediction results which obtained by detecting state information , the residual life of spare parts orderingwas taken as threshold to draft spares ordering decision strategy . Then, according to the theory of renewal process , the prescriptive availabilitywas selected as constraint , the expected cost per unit time was identified asoptimization goal to establish the optimization modelwhose optimization variableswere failure prediction intervals and sparepartsordering threshold .Then, according to the theory of renewal process , the prescriptive availabilitywas selected as constraint , the expected cost per unit time was identified asoptimization goal to establish the optimization modelwhose optimization variableswere failureprediction intervals and sparepartsordering threshold .Finally, the example is given to solve simulation and optimizationof the es-tablished model to obtainthe bestfailure prediction intervals and sparepartsordering threshold , which verifies the feasibility and effective-ness of the model .%针对退化状态分布函数未知的关键备件订购问题，考虑故障预测结果和备件订购相结合，提出一种基于故障预测的备件订购决策优化方法。首先，根据由状态检测信息得到的设备剩余寿命的预测结果，以备件订购时的剩余寿命为阈值制定备件订购决策策略；然后，根据更新过程理论，以规定可用度为约束条件，以单位时间内的期望费用最小为优化目标，建立以故障预测间隔期和备件订购阈值为优化变量的优化模型。采用人群搜索算法优化求解，得到系统最佳的故障预测间隔期和备件订购阈值。最后，通过引入算例，对所建模型优化仿真求解，得到设备最优的故障预测间隔期和备件订购阈值，验证了所建模型的可行性和有效性。