Statistical Investigation on Resistance Spot Welding Quality Using a Two-State, Sliding-Level Experiment

Abstract

Quality variation in resistance spot welding is a major concern in the automotive industry. The relationship between weld quality and various process conditions, including abnormal process conditions, has not yet been systematically studied. This paper investigates this relationship using a newly developed two-stage, sliding-level experiment. In the experiment, welding current is treated as a “slid factor” whose settings are determined based on those of other process variables. Engineering knowledge is applied in statistical model selection. From the analysis, it is found that abnormal process conditions, such as axial misalignment, angular misalignment, poor fitup, edge weld, and electrode wear, significantly affect weld size and thus cause large variation in the weld quality. Although they may help increase the weld size in some cases, abnormal process conditions generally lead to a less robust process. In order to minimize the effects of the abnormal process conditions, a robust parameter design is formulated using the statistical models developed from the experimental data. The analysis suggests that high current and large electrodes should be used for reducing the weld quality variation. Developed in this study, the new experimental design and analysis procedures can also be applied to other processes, where the process variables are inter-dependent.