Identification Method of Key Risk Control Points in Mechanical Product Assembly Process

Abstract

In order to improve the assembly process quality of mechanical products, a structuralized decomposition method of Function-Movement-Action (FMA) was used to obtain the meta-action (MA) of minimum assembly granularity of mechanical products. Secondly, taking the performance index of the moving layer as the object of assembly process quality analysis, the state space model of the hybrid type MA was established, and the relationship models between the quality of the serial, parallel and hybrid type assembly process and the internal influencing factors were given. Then, the Partial Least Squares Regression (PLSR) method was used to solve the problem of multicollinearity and small sample among the influencing factors of each MA, and the key risk control points in the assembly process were obtained by the importance index analysis of variable projection. Finally, the effectiveness of the proposed method is proved by taking a numerical control turntable as an example.