扰动环境下基于复杂网络的生产车间瓶颈分析  

The Workshop Bottleneck Analysis Based on Complex Network Under the Disturbance Environment

作　　者：李华华[1] 袁逸萍[1] 李晓娟[1] 

机构地区：[1]新疆大学机械工程学院,乌鲁木齐830047

出　　处：《组合机床与自动化加工技术》2016年第6期39-42,共4页Modular Machine Tool & Automatic Manufacturing Technique

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);新疆维吾尔自治区科技厅"十二五"重大专项(201130110-1)

摘　　要：针对生产车间扰动所造成的系统产出效率低下和瓶颈预测困难这一问题,提出基于耦合映像格子的制造瓶颈辨识方法。首先构造生产车间网络模型,建立扰动因素动力学方程,获取扰动因素流转的判定依据。综合考虑网络拓扑特性及工作站节点自身特性综合影响,提出基于CML(耦合映像格子)的瓶颈状态预测模型,通过matlab程序仿真进而实现扰动环境下瓶颈节点的动态识别。最后通过某汽车装配车间内实际的生产数据和ARENA仿真实例,验证了该方法的正确性和有效性。Aiming at the low of system output value caused by the disturbance of manufacture workshop and prediction problem of bottleneck under the disturbance environment,a bottleneck recognition method is proposed based on coupled map lattice. Firstly, structuring workshop network model,establishing dynamics equation of disturbance factors,Obtain the basis of judgment according to the flow factors. network topology characteristics is taken into account combined with the comprehensive influence of workstation nodes of its own characteristics, structuring workshop network model,proposing the bottleneck state prediction model basing on the CML,and the bottleneck nodes is identified by matlab simulation under disturbance environment.Finally, it is proved the accuracy and effectiveness of this method by the example of actual production data of automobile assembly workshop and ARENA simulation.

关 键 词：复杂网络 生产车间 扰动因素 瓶颈预测 耦合映像格子 

分 类 号：TH166[机械工程—机械制造及自动化] TG506[金属学及工艺—金属切削加工及机床]