Quality Control in Cocoa Powder Production Process: A Robust MSPC Approach

To monitor a multivariate process mean, Hotelling’s T^2 control chart is often used. However, the presence of multiple outliers may go undetected due to the masking effect or swamping effect. In this study, we propose a robust Hotelling’s T^2 control charts where the mean vector and the covariance matrix are estimated by using fast minimum covariance determinant (FMCD) which gives a high breakdown point estimates. This study found that the latter approach performs far better than the former in terms of the ability in detecting an out-of-control situation during the start-up stage. We present and discuss our experience in monitoring the process mean of cocoa powder production process in a Malaysian company located in Johor Bahru.