Fuzzy Mewma Control Chart with Median Transformation for Manufacturing Multivariate Process Control

The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is developed with the advantage of detecting small shifts in the mean vector and is robust. Conventional control charts have limitations in handling ambiguity in a process. The fuzzy MEWMA control chart is proposed to detect small shifts under uncertain conditions. When the fuzzy data distribution is asymmetric, the median transformation method is used. Quality control is crucial for the convection industry. Clothing designs tailored to human body proportions indicate that ambiguity in the process and small measurement shifts can affect measurement accuracy. This study will utilize the Fuzzy MEWMA control chart with median transformation for quality control in the multivariate manufacturing process, particularly in the convection industry. The purpose of this study is to determine the UCL value, obtain performance evaluation results and implement the Fuzzy MEWMA control chart with median transformation. The research findings show that the UCL with an alpha level cut of 0.6 for three quality characteristics increases as the lambda value decreases. Performance evaluation results indicate that when small process shifts occur, lambda 0.05 and lambda 0.1 provide better performance than other lambda values. The production control results for uniform manufacturing in a convection company in Palu City show two observations outside the UCL, which can serve as an early warning for the company.