现代民机产品普遍采用模块化设计，具有多层次特点，相应的维修场所也表现为多个维修级别。现有修理级别分析（LORA）模型在移级维修和报废时，可能存在父单元与其内部封装子单元成本重复累加的问题。引入跟随行为矩阵，对子单元中因父单元层级约束而做出的决策进行标记，能有效地避免父单元与子单元成本被重复计算。在此基础上，考虑实际维修活动中无故障发现事件（NFF）、二次维修等人为因素对LORA决策的影响，建立适用于民机的修理级别分析模型，较已有模型更加真实地反映决策的预计成本，提高了决策的可信度和工程适用性。最后使用混合惩罚函数法将原问题转化为等价的无约束优化问题，采用改进的二进制粒子群算法（BPSO）对多故障模式下的三层三级案例进行仿真优化，验证了该经济性分析模型的合理性和求解算法的有效性。
Modular design is widely used in modern civil aircraft products. It has multi-indenture characteristics, and its corresponding maintenance sites are also divided into multi-echelon maintenance levels. When the existing repair level analysis model is moved or discarded, it may have the problem of repeated accumulation of the cost of module and its internal packaging subunit. In this paper, the following behavior matrix is introduced to mark the decisions made by the hierarchy constraints of the parent unit, which can effectively avoid the repeated calculation of the costs of the parent-unit and the child-unit. On this basis, the influences of human factors such as No Fault Found (NFF) event and secondary maintenance on LORA’s decision aere considered when building the repair level analysis model suitable for civil aircraft. Compared with the existing model, the proposed model can more accurately reflect the estimated cost of decision-making more truly, not only improving the credibility of the decision but also increasing the applicability of the project. Finally, the mixed penalty function method is used to transform the original problem into an equivalent unconstrained optimization problem. An improved Binary Particle Swarm Optimization (BPSO) algorithm is used to simulate and optimize the three-indenture and three-echelon case with multi-fault mode. The results verified the rationality of the economic analysis model and the effectiveness of the algorithm.
[1] LUCAS C M. Level of repair analysis for the enhancement of maintenance resources in vessel life cycle sustainment[D]. Washington, D.C.:The George Washington University, 2018:2038-2043.
[2] 郭霖瀚, 王恺, 王严,等. 多级多层备件供应链需求建模与仿真[J]. 计算机集成制造系统, 2010, 16(10):2038-2043. GUO L H, WANG K, WANG Y, et al. Multi-indenture multi-echelon spare part supply chain requirement modeling and simulation[J]. Computer Integrated Manufacturing Systems, 2010, 16(10):2038-2043 (in Chinese).
[3] Department of Defense. Level of repair analysis:MIL-STD-1390D[S]. Washington, D.C.:Department of Defense, 1993.
[4] SAE. AS1390:Level of repair analysis[S]. Warrendale:SAE International, 2014.
[5] Department of Defense. Level of repair analysis:MIL-HDBK-1390[S]. Washington, D.C.:Department of Defense, 2015.
[6] 国防科学技术工业委员会.修理级别分析:GJB 2961-97[S]. 北京:国防科工委军标出版发行部, 1997. COSTIND. Level of repair analysis:GJB 2961-97[S]. Beijing:Armament Standard Press of Commission of Science Technology and Industry for National Defense, 1997 (in Chinese).
[7] BARROS L L. The optimization of repair decision using life-cycle cost parameters[J]. IMA Journal of Mathematics Applied in Business & Industry, 1998, 9(4):403-413.
[8] SARANGA H, KUMAR U D. Optimization of aircraft maintenance/support infrastructure using genetic algorithms-level of repair analysis[J]. Annals of Operations Research, 2006, 143(1):91-106.
[9] BASTEN R J I, SCHUTTEN J M J, HEIJDEN M C V D. An efficient model formulation for level of repair analysis[J]. Annals of Operations Research, 2009, 172(1):119-142.
[10] RAWAT M, LAD B K. Simultaneous selection of reliability design and level of repair for fleet systems[J]. International Journal of System Assurance Engineering and Management, 2016, 7(2):138-155.
[11] RAWAT M, LAD B K, DUFFUAA S, et al. An integrated Strategy for fleet maintenance planning[J]. Journal of Quality in Maintenance Engineering, 2017:457-479.
[12] 李良峰, 陈柏松, 王晓伟, 等. 国内外修理级别分析对比研究[J]. 装备制造技术, 2011(8):140-143. LI L F, CHEN B S, WANG X W, et al. Compare research on level of repair analysis both in China and abroad[J]. Equipment Manufacturing Technology, 2011(8):140-143 (in Chinese).
[13] 吴昊, 左洪福, 孙伟. 一种新的民用飞机修理级别优化模型[J]. 航空学报, 2009, 30(2):247-253. WU H, ZUO H F, SUN W. New level of repair analysis optimization model for civil aircraft maintenance[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(2):247-253 (in Chinese).
[14] 贾宝惠, 周帆. 基于遗传禁忌搜索混合算法的修理级别问题研究[J].机械工程与自动化, 2015(6):11-13. JIA B H, ZHOU F. Study on level of repair analysis based on hybrid genetic-tabu search algorithm[J]. Mechanical Engineering & Automation, 2015(6):11-13 (in Chinese).
[15] 贾宝惠, 于灵杰, 蔺越国,等. 基于AHP-SPA方法的民机修理级别确定综合分析模型[J]. 航空学报, 2017, 38(11):221130. JIA B H, YU L J, LIN Y G, et al. Comprehensive analysis model for determination of civil aircraft repair level based on AHP-SPA method[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(11):221130 (in Chinese).
[16] 薛陶, 冯蕴雯, 薛小锋,等. 装备修理级别与备件库存联合优化模型研究[J]. 机械科学与技术, 2015, 34(6):963-968. XUE T, FENG Y W, XUE X F, et al. Research on joint optimizing model of equipment LORA and spare parts inventory[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(6):963-968 (in Chinese).
[17] BASTON R J I, VANDER HEIJDEN M C, SCHUTTEN J M J, et al. Practical extensions to a minimum cost flow model for level of repair analysis[J]. European Journal of Operational Research, 2011, 211(2):333-342.
[18] BASTON R J I, SCHUTTEN J M J, VANDER HEIJD M C, et al. Level of repair analysis:A generic mode[R]. Enschede:Universiteit Twente, 2008.
[19] 乔亚琼. 飞机燃油系统智能化故障诊断方法研究[D]. 西安:西北工业大学, 2007. QIAO Y Q. Intelligent diagnosis method research on airplane fuel system[D]. Xi'an:Northwestern Polytechnical University, 2017 (in Chinese).
[20] 乔进军. 论航电设备"无故障发现"政策与控制[C]//中国航空学会航空维修工程专业分会. 航空装备维修技术及应用研讨会. 北京:国防工业出版社, 2015:225-230. QIAO J J. On the "no fault found" policy and control of avionics equipment[C]//China Aviation Society Aviation Maintenance Engineering Branch. Aviation Equipment Maintenance Technology and Application Seminar. Beijing:National Defense Industry Press, 2015:225-230 (in Chinese).
[21] KENNEDY J, EBERHART R C. A discrete binary version of the particle swarm algorithm[C]//1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation. Piscataway, NJ:IEEE Press, 1997:4104-4108.
[22] LI Z, LI N. A novel multi-mutation binary particle swarm optimization for 0/1 knapsack problem[C]//Chinese Control and Decision Conference, 2009:3042-3047.
[23] PEDRASA M, SPOONER T D, MACGILL I F, et al. Scheduling of demand side resources using binary particle swarm optimization[J]. IEEE Transactions on Power Systems, 2009, 24(3):1173-1181.
[24] MIRJALILI S, LEWIS A. S-shaped versus V-shaped transfer functions for binary particle swarm optimization[J]. Swarm and Evolutionary Computation, 2013, 9:1-14.
[25] 薛陶, 冯蕴雯, 薛小锋,等. 一种飞机修理级别经济性分析模型[J]. 航空学报, 2013, 34(1):97-103. TAO X, FENG Y W, XUE X F, et al. An aircraft economic evaluation model for level of repair analysis[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(1):97-103 (in Chinese).
CJA