首页|异构负载下单机调度与预测性维修的集成建模

异构负载下单机调度与预测性维修的集成建模

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在生产调度的过程中，设备常常因加工不同作业而承受不同负载即异构负载，设备受异构负载的影响导致其加工每项作业过程中的退化速率不同，从而影响生产调度与维修计划的排程，进而带来资源闲置和时间成本增加的问题。为了解决该问题，在考虑异构负载影响下，提出单机调度与预测性维修的联合策略，以最小总加权期望完成时间为目标构建相应的集成模型。对单机调度过程中受异构负载影响的设备，建立基于维纳过程的退化模型，根据其退化规律，推导相应设备剩余寿命的累积分布函数。通过数值实验，分别针对异构负载与平均负载的情况比较相应集成模型的优化结果，结果表明了在集成模型中考虑异构负载的必要性，并通过参数灵敏度分析验证了所建集成模型的有效性。
Integrated modeling of stand-alone scheduling and predictive maintenance under heterogeneous loads
In the process of production scheduling,equipment often bears different loads due to processing different jobs,that is,heterogeneous loads.Due to the impact of heterogeneous loads,the degradation rate of the equipment in each operation is different,which will affect production scheduling and maintenance planning,resulting in idle resources and increased time costs.To solve this problem,a joint strategy of single machine scheduling and predictive maintenance is formulated considering the impact of heterogeneous loads.On this basis,an integrated model is established to minimize the total weighted expected completion time.A degradation model based on the Wiener process is established for the equipment affected by the heterogeneous load in the single machine scheduling process.And the cumulative distribution function of the remaining useful life of the equipment is derived.Numerical experiments are conducted to compare the optimization results of the corresponding integration models of the conditions of heterogeneous load with the average load respectively,which indicates that it is necessary to consider heterogeneous load in the integration model.And the sensitivity analysis of the parameters verifies the effectiveness of the integrated model.

heterogeneous loadsingle machine dispatchingpredictive maintenanceWiener processresidual life predictionintegration model

甘婕、舒坦、石慧、赵春晓

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太原科技大学工业与系统工程研究所,太原 030024

山西人文社科重点研究基地装备制造业创新发展研究中心,太原 030024

异构负载 单机调度 预测性维修 维纳过程 剩余寿命预测 集成模型

国家自然科学基金山西省高等学校人文社会科学重点研究基地项目山西省自然科学基金面上项目山西省高等学校教学改革创新项目山西省高等学校科技创新项目太原科技大学研究生联合培养示范基地项目

720711832021010220210302123206J20205002021L322JD2022010

2024

10.13195/j.kzyjc.2022.0943

控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子：1.227
ISSN：1001-0920
年,卷(期)：2024.39(3)
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