非完美维修情境下的预防性维修多目标决策模型

doi:10.16183/j.cnki.jsjtu.2018.05.003

摘要/Abstract

摘要： 针对复杂装备预防性维修决策中设备寿命和成本估计不足的问题，研究了非完美维修情境下复杂装备的预防性维修决策优化方法.基于虚拟寿命理论建立了维修效率与设备寿命之间的关系，提出了3种检测及维修的周期计算方法；将故障导致的质量波动及可变维修成本纳入考量，建立了更精确的成本估算模型；以设备可用度最高和总成本率最低为目标，建立了预防性维修的多目标决策模型.同时，以某型加工中心为例，结合其生产与维修历史记录，通过实例数值对比分析了静态、动态及失效极限3种维护周期计算方法及其适用性，以及不同维修水平下总成本率与设备可用度的差异，并分析了质量成本对最优策略的影响，从而验证了所建模型的可靠性和新颖性.

关键词: 设备, 预防性维修, 非完美维修, 质量成本, 多目标决策

Abstract: The preventive maintenance (PM) decision-optimization problem of complex equipment is studied under imperfect repair context aiming at the deficiencies of residual life prediction and cost estimation. Based on the virtual age theory, we built the relationship between maintenance efficiency and equipment age. Furthermore, three different methods are put forward to calculate the relation between checking intervals and maintenance period. The quality fluctuation and variable maintenance cost caused by fault are considered to build a more concise overall cost estimation model. A multi-objective decision-making model for preventive maintenance is established to ensure high availability of equipment and low total cost. Numerical verification is performed using the production and maintenance history data of a machining center. The verification intends to compare the different overall cost rate and equipment availability under static, dynamic and failure limits calculation methods and various maintenance levels. In the same way, the applicability of the three methods is discussed. The influence of the quality cost on the optimal strategy is analyzed to prove the advanced nature of the method.

Key words: equipment, preventive maintenance, imperfect repair, quality cost, multi-objective decision

中图分类号:

TH 17

郝虹斐1，郭伟1，桂林2，王磊1. 非完美维修情境下的预防性维修多目标决策模型[J]. 上海交通大学学报（自然版）, 2018, 52(5): 518-524.

HAO Hongfei1,GUO Wei1,GUI Lin2,WANG Lei1. A Multi-Objective Preventive Maintenance Decision-Making Model for Imperfect Repair Process[J]. Journal of Shanghai Jiaotong University, 2018, 52(5): 518-524.

参考文献

［1］SHAFIEE M, CHUKOVA S. Maintenance models in warranty: A literature review［J］. European Journal of Operational Research, 2013, 229(3): 561-572. ［2］GILARDONI G L, TOLEDO DE TOLEDO M L, FREITAS M A, et al. Dynamics of an optimal maintenance policy for imperfect repair models［J］. European Journal of Operational Research, 2016, 248(3): 1104-1112. ［3］石慧, 曾建潮. 基于寿命预测的预防性维护维修策略［J］. 计算机集成制造系统, 2014, 20(5): 1133-1140. SHI Hui, ZENG Jianchao. Preventive maintenance strategy based on life prediction［J］. Computer Integrated Manufacturing Systems, 2014, 20(5): 1133-1140. ［4］石慧, 曾建潮. 考虑非完美维修的实时剩余寿命预测及维修决策模型［J］. 计算机集成制造系统, 2014, 20(9): 2259-2266. SHI Hui, ZENG Jianchao. Prediction of real-time remaining useful life and maintenance decision model considering imperfect preventive maintenance［J］. Computer Integrated Manufacturing Systems, 2014, 20(9): 2259-2266. ［5］CHENG C Y, ZHAO X F, CHEN M C, et al. A failure-rate-reduction periodic preventive maintenance model with delayed initial time in a finite time period［J］. Quality Technology & Quantitative Management, 2014, 11(3): 245-254. ［6］LEE H, CHA J H. New stochastic models for preventive maintenance and maintenance optimization［J］. European Journal of Operational Research, 2016, 255(1): 80-90. ［7］裴洪, 胡昌华, 司小胜, 等. 不完美维护下基于剩余寿命预测信息的设备维护决策模型［J］. 自动化学报, 2018, 44(4): 719-729. PEI Hong, HU Changhua, SI Xiaosheng, et al. Remaining life prediction information-based maintenance decision model for equipment under imperfect maintenance［J］. Acta Automatica Sinica, 2018, 44(4): 719-729. ［8］XIA T, JIN X, XI L, et al. Operating load based real-time rolling grey forecasting for machine health prognosis in dynamic maintenance schedule［J］. Journal of Intelligent Manufacturing, 2015, 26(2): 269-280. ［9］NOURELFATH M, NAHAS N, BEN-DAYA M. Integrated preventive maintenance and production decisions for imperfect processes［J］. Reliability Engineering & System Safety, 2016, 148: 21-31. ［10］DA W, FENG H X, PAN E S. Integrated preventive maintenance and production scheduling optimization on uniform parallel machines with deterioration effect［C］∥International Conference on Industrial Engineering and Engineering Management. Bali, Indonesia: IEEE, 2016. ［11］ZHANG X H, ZENG J C. Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems［J］. European Journal of Operational Research, 2017, 262(2): 479-498. ［12］夏唐斌, 周晓军, 奚立峰. 基于失效率调整因子的多目标动态预防性维护决策建模［J］. 上海交通大学学报, 2009, 43(5): 821-824. XIA Tangbin, ZHOU Xiaojun, XI Lifeng. Multi-attribute model for dynamic preventive maintenance decision with hybrid evolution factors［J］. Journal of Shanghai Jiao Tong University, 2009, 43(5): 821-824. ［13］XIA T B, JIN X N, Xi L F, et al. Production-driven opportunistic maintenance for batch production based on MAM-APB scheduling［J］. European Journal of Operational Research, 2015, 240(3): 781-790. ［14］陶辛阳, 夏唐斌, 奚立峰. 基于健康指数的预防性维护与多目标生产调度联合优化建模［J］. 上海交通大学学报, 2014, 48(8): 1170-1174. TAO Xinyang, XIA Tangbin, XI Lifeng. Health-index-based joint optimization of preventive maintenance and multi-attribute production scheduling［J］. Journal of Shanghai Jiao Tong University, 2014, 48(8): 1170-1174. ［15］崔维伟, 陆志强, 潘尔顺. 基于多目标优化的生产调度与设备维护集成研究［J］. 计算机集成制造系统, 2014, 20(6): 1398-1404. CUI Weiwei, LU Zhiqiang, PAN Ershun. Production scheduling and preventive maintenance integration based on multi-objective optimization［J］. Computer Integrated Manufacturing Systems, 2014, 20(6): 1398-1404. ［16］NOURELFATH M, CHTELET E. Integrating production, inventory and maintenance planning for a parallel system with dependent components［J］. Re-liability Engineering & System Safety, 2012, 101: 59-66. ［17］ZHOU X J, WU C J, LI Y T, et al. A preventive maintenance model for leased equipment subject to internal degradation and external shock damage［J］. Reliability Engineering & System Safety, 2016, 154: 1-7. ［18］丁珮雯, 蒋祖华, 胡家文, 等. 带有交货期时间窗的生产与维护联合调度优化［J］. 上海交通大学学报, 2015, 49(4): 524-530. DING Peiwen, JIANG Zuhua, HU Jiawen, et al. Integrating production scheduling and preventive maintenance for a single machine with due window［J］. Journal of Shanghai Jiao Tong University, 2015, 49(4): 524-530. ［19］CHEN Z, LI Y P, PAN E S. Joint optimization of degradation-based burn-in, quality, and preventive maintenance［C］∥International Conference on Industrial Engineering and Engineering Management. Bali, Indonesia: IEEE, 2016. ［20］DOYEN L, GAUDOIN O. Classes of imperfect repair models based on reduction of failure intensity or virtual age［J］. Reliability Engineering & System Safety, 2004, 84(1): 45-56. ［21］NGUYEN D T, DIJOUX Y, FOULADIRAD M. Analytical properties of an imperfect repair model and application in preventive maintenance scheduling［J］. European Journal of Operational Research, 2017, 256(2): 439-453.

[1]	许勇, 蔡云泽, 宋林. 基于数据驱动的核电设备状态评估研究综述[J]. 上海交通大学学报, 2022, 56(3): 267-278.
[2]	陈欣, 赵晓磊, 王立坤, 肖德明, 张腾月. 深水大型吸力锚建造技术研究[J]. 海洋工程装备与技术, 2022, 9(1): 32-36.
[3]	钟小波, 于龙, 吕顺, 牟文通, 朱岩峰. 秦山核电功能设备组的创建及应用[J]. 上海交通大学学报, 2021, 55(S2): 1-6.
[4]	翟海保, 韩博文, 吴国松. 面向电网调度设备监控的智能搜索框架技术[J]. 上海交通大学学报, 2021, 55(S2): 15-21.
[5]	卢东祁, 张乾, 徐一洲, 鲍杰利, 罗芬. 面向电力物联网的终端设备适配接入研究[J]. 上海交通大学学报, 2021, 55(S2): 72-76.
[6]	宁小涵, 周晓军. 考虑随机生产等待的串行生产系统机会维护建模[J]. 上海交通大学学报, 2021, 55(10): 1281-1290.
[7]	齐东润, 陈刚. 无人驾驶机器人多目标模糊操纵策略[J]. 上海交通大学学报, 2021, 55(10): 1310-1319.
[8]	方佳, 陆志强. 考虑设备故障的鲁棒调度计划模板的建模优化[J]. 上海交通大学学报, 2020, 54(12): 1278-1290.
[9]	苏春，赵家彬. 基于产品使用率的柔性基本质保策略优化设计[J]. 上海交通大学学报, 2020, 54(11): 1182-1188.
[10]	俞梦琦，史凯龙，周晓军. 基于双时间窗的多设备串行系统机会维护策略[J]. 上海交通大学学报, 2020, 54(1): 69-75.
[11]	李华桥，吴霄，代俊安，穆兰芬，徐信哲. PDCA循环在提高仪控设备断路器系统抗冲击能力中的运用[J]. 上海交通大学学报, 2019, 53(Sup.1): 61-67.
[12]	张明浩, 田从永, 李家军, 杨青峰, 刘荣坤, 杨建昌. LNG核心工艺模块大型设备安装尺寸控制测量技术探讨[J]. 海洋工程装备与技术, 2019, 6(2): 530-535.
[13]	吴松平, 丰兴盛, 赵鑫磊, 刘焕龙, 杨震. 大型鞍座设备侧装工艺的优化及工程应用[J]. 海洋工程装备与技术, 2018, 5(增刊): 276-278.
[14]	余勇林, 张云, 陈志宇, 张远飞. 电力推进系统配置研究[J]. 海洋工程装备与技术, 2018, 5(增刊): 164-168.
[15]	宋杰, 马宁, 李昱浩, 葛嘉垚. 船舶设备数据库软件系统开发[J]. 海洋工程装备与技术, 2018, 5(5): 359-366.