Abstract: To effectively control the quality variation of manufacturing process,a variation source identification methodology 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 identification 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 characteristics of manufacturing processes was obtained.To verify the scientificity and practicality of the proposed methodology,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.

Key words: manufacturing processes, variation, joint probability density, likelihood functions, aircraft panel components

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。

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