面向数字化工厂的需求结构多目标决策控制研究  

Multi-object decision control of requirement structure for digital factory

作　　者：崔剑[1] 陶俐言[1] 

机构地区：[1]杭州电子科技大学管理学院,浙江杭州310018

出　　处：《机电工程》2012年第10期1150-1153,1182,共5页Journal of Mechanical & Electrical Engineering

基　　金：国防基础科研计划资助项目(A3920110001);杭州电子科技大学科研资助项目(KYS035610018)

摘　　要：针对数字化工厂需求结构多目标的优化控制问题,提出了数字化工厂设计、制造、装配、物流等各个节点需求结构多目标决策控制模型。采用数学函数形式表达,并描述了数字化工厂各节点需求结构决策因素,分析了多目标决策的控制优化过程;以汽轮机产品为例,应用基于Pareto的熵算法对数字化工厂需求结构进行了多目标优化求解,确定了多目标决策指标权系数,以权衡需求结构多目标的任务实施。研究结果表明,该模型验证了数字化工厂多目标需求结构决策控制理论,Pareto熵算法优化了需求结构实施的控制过程,在满足客户需求的基础上,合理配置了企业的需求结构资源。Aiming at realizing the optimal control on multi-object requirement structure in digital factory（DF）,the model of multi-object decision control on requirement structure was put forward in every node, such as design, manufacture, assemble, logistics and so on. The form of math function was presented to depict the structure decision factor in every node, and the optimal process of multi-object decision was analyzed. The example of steam turbine was applied concretely to verify the model theory, entropy arithmetic based on Pareto was applied to the index coefficient of multi-object decision, the index weight coefficient of multi-objective was determined, the task implementation was weighed. The results indicate that model research validates the control theory of multi-object demand structure in digital factory, and the research on structure multi-object decision control for digital factory optimizes the structure resource of system implementation on the basis of meeting greatly customer requirement.

关 键 词：数字化工厂 需求结构 多目标决策控制 PARETO 

分 类 号：TH186[机械工程—机械制造及自动化]