How to improve the scrap rate in data control modules using the DMAIC model and statistical analysis

Six Sigma represents a methodology designed for error-free processes throughout a company. It provides great statistical tools and the DMAIC systematic model which help reduce process variation in many different manufacturing companies, especially in the automotive domain. The present study aims to improve the failure rate in body control modules dealing with electrical overstress (EOS) caused by electrostatic discharge (ESD) events, in an automotive company situated in the Western part of Romania. Thirty hypotheses were taken in consideration and analyzed using statistical tools like correlation, regression, and trend analysis together with quality tools like Ishikawa diagram or Pareto analysis in a DMAIC approach. The corrective actions which were brought to the process were monitored to assure an acceptable process capability. The improvement actions decreased considerably the overall scrap rate. The results show that for the specific analyzed error message, the scrap costs have been reduced by 98.71%.