考虑订单不确定性的Job-Shop网络鲁棒性研究  

Robustness of Job-Shop Networks Considering Order Uncertainty

作　　者：李晓艳[1] 李明[1] 袁逸萍[1] 李晓娟[1] LI Xiao-yan;LI Ming;YUAN Yi-ping;LI Xiao-juan(School of Mechanical Engineering,Xinjiang University,Xinjiang Urumqi830047,China)

机构地区：[1]新疆大学机械工程学院,新疆乌鲁木齐830047

出　　处：《机械设计与制造》2020年第7期43-45,50,共4页Machinery Design & Manufacture

基　　金：国家自然科学基金(51365054);新疆维吾尔自治区自然科学基金(2014211A008)。

摘　　要：针对订单不确定性对作业车间的鲁棒性的影响问题,首先,从复杂网络视角描述生产过程,建立作业车间网络模型,并对建立的有向加权作业车间网络的关键特征参数进行定义;其次,考虑生产特性和网络特征构造基于耦合映像格子的鲁棒性模型,利用网络中级联失效的进程与规模建立作业车间的鲁棒性评价指标,最后以实际生产过程为例进行仿真验证,结果表明,不同的扰动强度和扰动策略对网络的影响不同,也说明了该方法对作业车间的鲁棒性评价有效可行,且鲁棒性模型有较好的并行计算特性。Aiming at the influence of order uncertainty on the robustness of job shop,Firstly,description of production process from the perspective of complex network,establishment of job shop network model and the key feature parameters are defined based on the established weighted job shop network.Secondly,considering the production characteristics and network characteristics constructed a robust model based on Coupled Map Lattices(CML),robustness evaluation standard of job shop based on process and scale of network cascading failure.Finally,the actual production process is taken as an example to verify the simulation,the results show that different disturbance intensity and disturbance strategy have different effects on the network,and the method is effective and feasible for evaluating the robustness of job shop and the robustness model has good parallel computing characteristics.

关 键 词：订单不确定 JOB-SHOP 复杂网络 耦合映像格子 鲁棒性 

分 类 号：TH16[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]