协同制造链的系统不确定性分析与建模  

Analysis and modeling of system uncertainties in collaborative manufacturing chains

作　　者：罗国富[1] 李浩[1,2] 马军[1] 肖艳秋[1] 钱力 

机构地区：[1]郑州轻工业学院机电工程学院,郑州450002 [2]浙江大学机械工程学系,杭州310027 [3]河南省电力勘测设计院,郑州450052

出　　处：《高技术通讯》2011年第9期954-961,共8页Chinese High Technology Letters

基　　金：863计划（2009AA04Z146）,河南省科技攻关（084100510014）和郑州市科技攻关（084100510014）资助项目.

摘　　要：针对协同制造链（CMC）中存在大量不确定性的问题，分析了CMC运行过程中出现的不确定性及其来源，建立了不确定性数学模型和传播模型。通过对系统不确定性评价与预测过程的分析，提出了基于故障树分析法进行系统不确定度评定的贝叶斯模型，给出了具体评价过程，实现了CMC的不确定性评价与预测，并采用案例验证了该方法的可行性。CMC的不确定性模型与不确定度的评价方法能为产品协同制造不确定性的认识、评估和控制提供一种实用的分析方法和决策依据。Aiming at the existence of many uncertainties in collaborative manufacturing chains （ CMC）, the analyses of the uncertainties in CMC running processes and the sources of them were concluded, and the mathematical model and the propagation model of CMC systems＇ s uncertainties were built. Based on analyzing the assessment and forecasting process of system uncertainties, a Bayes model based on fault tree analysis（FTA） for assessment of uncertainties was proposed, and the assessment process was given in detail. The practical assessment and forecasting of CMC uncertainties were carried out, and an application case of the model showed that it was feasible. The uncertainty model and the uncertainty assessment method for CMC systems could provide a practical basis for understanding, evaluating and controling the uncertainties of CMC systems.

关 键 词：协同制造链(CMC) 协同制造单元 不确定性 故障树分析法 贝叶斯方法 建模 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]