ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Joint Optimization of Maintenance and Inventory in Equipment Autonomic Logistics
Received date: 2012-10-15
Revised date: 2013-01-21
Online published: 2013-02-18
Supported by
National Natural Science Foundation of China(51175502)
The core of an autonomic logistics system (ALS) is to accomplish optimal maintenance and support decision driven by the remaining useful life estimation (RULE) information under a networked logistics architecture, which can decrease life cycle cost and improve average operational availability. First, the characteristics of RULE and the operational mechanism of ALS are presented, and the cost generation mechanisms of equipment maintenance and spare part replenishment of ALS are analyzed. Then, a joint optimization model of maintenance and inventory based on RULE is proposed to minimize the long-term average cost rate. Finally the arithmetic for optimal logistics strategies is designed using Monte Carlo simulation methods which can measure the effect of miss detection rate and false alarm rate of RULE on logistics performance.
XU Yuguo , QIU Jing , LIU Guanjun . Joint Optimization of Maintenance and Inventory in Equipment Autonomic Logistics[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013 , 34(8) : 1864 -1873 . DOI: 10.7527/S1000-6893.2013.0072
[1] Zohrul K A, Farrash S H. Simulation of an integrated age replacement and spare provisioning policy using SLAM. Reliability Engineering & System Safety, 1996, 52(2): 129-138.
[2] Zohrul K A, Al-Olayan A S. Stocking policy for spare part provisioning under age based preventive replacement. European Journal of Operational Research, 1996, 90(1): 171-181.
[3] Dohi T, Shibuya T, Osaki S. Models for 1-out-of Q systems with stochastic lead times and expedited ordering options for spares inventory. European Journal of Operational Research, 1997, 103(1): 255-272.
[4] Chelbi A, Ait-Kadi D. Spare provisioning strategy for preventively replaced systems subjected to random failure. International Journal of Production Economics, 2001, 74(1-3): 183-189.
[5] Diallo C, Ait-Kadi D, Chelbi A. (s,Q) spare parts provisioning strategy for periodically replaced systems. IEEE Transactions on Reliability, 2008, 57(1): 134-139.
[6] Tu F, Ghoshal S, Luo J, et al. PHM integration with maintenance and inventory management systems. Proceedings of 2007 IEEE Aerospace Conference, 2007: 1-12.
[7] Elwany A H, Gebraeel N Z. Sensor-driven prognostic models for equipment replacement and spare parts inventory. IIE Transactions, 2008, 40(7): 629-639.
[8] Kaiser K M. A simulation study of predictive maintenance policies and how they impact manufacturing systems. Iowa City: Department of Mechanical and Industrial Engineering, University of Iowa, 2007.
[9] Kaiser K A, Gebraeel N Z. Predictive maintenance management using sensor-based degradation models. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, 2009, 39(4): 840-849.
[10] Armstrong M J, Atkins D R. Note on joint optimization of maintenance and inventory. IIE Transactions, 1998, 30(2): 143-149.
[11] Armstrong M J, Atkins D R. Joint optimization of maintenance and inventory policies for a simple system. IIE Transactions, 1996, 28(5): 415-424.
[12] Rausch M, Liao H. Joint production and spare part inventory control strategy driven by condition based maintenance. IEEE Transactions on Reliability, 2010, 59(3): 507-516.
[13] Khalak A, Tierno J. Influence of prognostic health management on logistic supply chain. Proceedings of 2006 American Control Conference, 2006: 3737-3742.
[14] Wang L. Models and methods for maintenance decisions:theory and applications. Hangzhou: College of Information Science and Engineering, Zhejiang University, 2007.(in Chinese) 王凌. 维修决策模型和方法的理论与应用研究. 杭州: 浙江大学信息科学与工程学院, 2007.
[15] Wang L, Chu J, Mao W. A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure. European Journal of Operational Research, 2009, 194(1): 184-205.
[16] Wang L, Chu J, Mao W. An optimum condition-based replacement and spare provisioning policy based on Markov chains. Journal of Quality in Maintenance Engineering, 2008, 14(4): 387-401.
[17] Wang W, Liu Y, Pecht M. A theoretical model to minimize the operational cost for canary-equipped electronic system's health management. Proceedings of the First International Symposium on System Informatics and Engineering, 2011: 233-238.
[18] Wang T, Lee J. On performance evaluation of prognostics algorithms. Proceeding for 63nd Meeting of the Society for Machinery Failure Prevention Technology, 2009: 219-226.
[19] Banjevic D. Remaining useful life in theory and practice. Metrika, 2009(69): 337-349.
[20] Rausch M T. Condition based maintenance of a single system under spare part inventory constraints. Wichita: Department of Industrial Engineering, Wichita State University, 2008: 36-40.
[21] Wang X N, Pi J M, Yu W, et al. A method of information efficiency evaluation in NCW. Modern Defence Technology, 2007, 35(5): 14-18.(in Chinese) 王小念, 皮军明, 余巍, 等. 一种网络中心战中信息效能度量方法. 现代防御技术, 2007, 35(5): 14-18.
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