• 论文 •    

面向维修的复杂装备模块智能聚类与优化求解技术

郏维强,冯毅雄,谭建荣,安相华,赵鑫   

  1. 1.浙江大学 流体动力与机电系统国家重点实验室,浙江杭州310027;2.大连重工起重集团有限公司,辽宁大连116013;3.华为技术有限公司杭州研究所,浙江杭州310051
  • 出版日期:2012-11-15 发布日期:2012-11-25

Intelligent clustering and optimal solving technology for complex equipment modules oriented to maintenance properties

JIA Wei-qiang, FENG Yi-xiong, TAN Jian-rong, AN Xiang-hua, ZHAO Xin   

  1. 1.State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou 310027, China;2.Dalian Heavy Industry Group Co., Ltd., Dalian 116013, China;3.Hangzhou Research Institute, Huawei Technology Limited, Hangzhou 310051, China
  • Online:2012-11-15 Published:2012-11-25

摘要: 为解决传统维修过程中由单独的维修部门被动应对既成事实的复杂装备检修问题,同时加强其他部门对于维修活动的协同能力,在复杂装备的设计阶段引入维修相关的驱动要素和维修阶段的策略选择,提出一种面向维修的复杂装备模块化设计方法。从维修成本、维修复杂度、维修效率等方面探讨复杂装备模块化设计准则,得到各维修特性的量化计算方法,通过综合考虑约束条件建立面向维修的模块化设计模型。采用青蛙跳跃算法和细菌优化相结合的混合多目标蛙跳算法对模型进行优化求解,从而得到一系列代表模块化设计方案的Pareto最优解,并利用基于信息熵理论的Pareto优选方法获取最终的模块化设计方案。以沈阳某机床厂设计生产的GMC型精密五轴加工中心为例,运用数值仿真手段验证了该方法的有效性和可行性。

关键词: 模块化设计, 维修, 多目标优化, 混合多目标蛙跳算法

Abstract: To overcome the shortage that single maintenance department participated in existing maintenance activities, the driven factors and strategy selection of maintenance stage were introduced in design stage of complex equipment, and modular design method of complex equipment oriented to maintenance was proposed. From the perspectives of maintenance cost, maintenance complexity and maintenance efficiency, the criteria for modular design were discussed, and specific calculation methods of maintenance properties were obtained. The modular design optimization model oriented to maintenance was constructed by considering constraint conditions. The model was optimized and solved by using hybrid multi-objective shuffled frog leaping algorithm which combined shuffled frog leaping algorithm with bacteria optimization, therefore a series of Pareto optimal solution which represented modular design schemes were obtained. The final modular design scheme was gained by using information entropy theory based Pareto optimized method. GMC precise 5-axis machining center in Shenyang machine tool factory was taken as an example to verify the effectiveness and feasibility of proposed method.

Key words: modular design, maintenance, multi-objective optimization, hybrid multi-objective shuffled frog leaping algorithm, Pareto solution sets

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