多元非线性制造过程波动源识别模型与方法  

Variation source identification methodology for multivariate nonlinear manufacturing processes

作　　者：汪邦军[1,2] 佘元冠[2] 戴伟[3] 刘宇[4] WANG Bangjun SHE Yuanguan DAI Wei LIUYu(Aero Engine Academy of China, Beijing 101304, China Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China School of Reliability and Systems Engineering, Beihang University Beijing 100191 ,China School of Economics and Management, Beijing Information Science ~Technology University, Beijing 100085, China)

机构地区：[1]中国航空发动机研究院,北京101304 [2]北京科技大学东凌经济管理学院,北京100083 [3]北京航空航天大学可靠性与系统工程学院,北京100191 [4]北京信息科技大学经济管理学院,北京100085

出　　处：《计算机集成制造系统》2017年第4期825-835,共11页Computer Integrated Manufacturing Systems

基　　金：北京市自然科学基金(青年项目)资助项目(9144028)~~

摘　　要：为有效控制产品制造过程的质量波动,提出一种多元非线性制造过程波动源识别模型和方法。该方法中的波动源识别综合框架对应一套零件几何特征的向量表示、零件模型、零件波动模型、波动源识别广义模型,利用多元联合概率密度、似然函数和似然比分析,得到最主要波动源判断准则,实现对多元非线性情况下影响产品制造过程的关键质量特性的主要波动源的识别。为验证该方法的科学性和可实践性,结合某飞机壁板组件波动源识别案例编写了MATLAB程序,并对有关模型、算法和流程进行了验证,保证了该方法在企业层面可行。To effectively control the quality variation ot manufacturing process, a variation source identlhcatlon meth- odology for multivariate nonlinear manufacturing processes was presented. A variation source identification frame corresponded to the vector representation, part models, part variation models, and general variation source identifi- cation equation of a set of geometric feature. By using approaches of joint probability density functions, likelihood functions and likelihood ratio comparison, the judgment criterion to identify the main variation source of key charac- teristics of manufacturing processes was obtained. To verify the scientificity and practicality of the proposed meth- odology, a case study on aircraft panel components was studied by writing MATLAB program to identify the main variation source, and the result showed the feasibility of this methodology at the enterprise level.

关 键 词：制造过程 波动 联合概率密度 似然函数 飞机壁板组件 

分 类 号：TG659[金属学及工艺—金属切削加工及机床]