A Systematic Study of the Prediction Model for Operator-Induced Assembly Defects Based on Assembly Complexity Factors

Abstract

It is a common view that the assembly process heavily affects a product's final quality and cost. The continuously shortening product life cycle requires a faster response speed as well as a lower defect rate in assembly production. In this situation, assembly quality control is becoming one of the most demanding problems in the modern manufacturing environment. The main causes of assembly defects can be classified into four categories, i.e., improper design, defective part, variance in assembly system, and operator error. The first three categories have been studied for many decades. However, elements of the operator error have not been fully explored. In this paper, using a copier assembly as an example, the problem of assembly defects caused by mistakes of operators is investigated systematically. A novel defect-rate prediction model is derived from the study of two complexity factors, namely, the design-based assembly complexity factor and the process-based assembly complexity factor, which are defined according to the structure and production characteristics of the copier. Several case studies consistently demonstrate that the new prediction model is accurate and stable for evaluating the copier assembly quality. Moreover, another case study offered in this paper demonstrates that the prediction model can provide effective assistance in the improvement of assembly quality.