Process yield improvement on the gram load adjusting process of a suspension manufacturer

This paper presents the improvement on the process yield of gram load adjustment by utilizing the six sigma concept. In define phase, the objective of this study is to increase the yield of this process. Currently, a process yield is 98.59%. The root cause analysis tools including Cause & Effect Diagram, Cause & Effect Matrix, and FMEA are employed to determine the key process input variables (KPIVs). There are 6 potential KPIVs selected into this study. Then, the design of experiment is conducted to investigate the effect of these KPIVs to the mean and variance of gram load after adjustment. A single replicate of 2^6-1 fractional factorial design with 4 center points is also performed. The results from the statistical analysis shows that both main and interaction effects have significant influence to the mean and variance of gram load of the suspension while there is no curvature effect to the response variables. The optimal process parameter is obtained and can increase process yield of selected machine from 98.59% to 99.14%.