上海交通大学 机械与动力工程学院， 上海 200240
出版日期:2019-04-28发布日期:2019-04-28通讯作者:夏唐斌，副教授，博士生导师，电话（Tel.）：021-34208589；E-mail：xtbxtb@sjtu.edu.cn.作者简介:司国锦（1995-），女，陕西省西安市人，博士，主要研究方向为制造系统的可靠性建模与维护决策.基金资助:国家自然科学基金资助项目（51875359,51535007），临港地区智能制造专项（ZN2017020102），国家市场监督管理总局质量基础设施效能研究重点实验室2018年开放课题（KF20180302）Triple-Level Opportunistic Maintenance Optimization Policy for Multi-Location Operation and Maintenance of Leasehold Service Network
SI Guojin,XIA Tangbin,SONG Ya,XI LifengSchool of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Online:2019-04-28Published:2019-04-28摘要/Abstract
摘要： 针对当前设备供应商提供全球维护服务中存在的租赁服务网络的广域运维问题，提出设备层、系统层、网络层动态交互的3层机会维护调度策略.根据各台设备的独立健康演化趋势，实时地规划设备层的预知维护时间间隔；基于贯序的设备层输出，在系统层进行优化调度并输出成组维护方案；基于各租赁产线的维护需求，在网络层解决租赁服务需求和维护资源约束之间的供需矛盾问题.根据调度特点建立数学优化模型，动态地更新决策向量和状态向量，并由此提出3层机会维护调度策略，得出层次递进的交互求解算法.通过算例分析，验证所提出的调度策略在广域运维领域的可行性和有效性.
关键词: 机会维护, 租赁服务网络, 利润优化, 广域运维
Abstract: This study focuses on the multi-location operation and maintenance problem of the leasehold service network where original equipment manufacturers provide global maintenance services. We propose an opportunistic maintenance optimization policy with dynamic interactions between the machine level, the system level and the network level. According to individual health evolutions of leased machines, preventive maintenance intervals are scheduled at the machine level. At the system level, group maintenance schemes are arranged by using leasing profit optimization. By pulling the requirements of multi-location leased lines, the balancing of lease service demand and maintenance resource constraint is handled at the network level. Therefore, a triple-level opportunistic maintenance policy is developed and an alternating algorithm based on hierarchical progression is then designed. Through arithmetic analysis, this proposed policy is proved to be effective and feasible.
Key words: opportunistic maintenance, leasehold service network, profit optimization, multi-location operation and maintenance
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