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.