Enhancing multivariate process control using partial least squares: a novel strategy for managing multiple output variables
摘要
In this study, we aim to control several customer characteristics by leveraging the properties of upstream manufacturing processes. We introduce an innovative approach that combines an enhanced Partial Least Squares (PLS) regression technique, tailored to output vectors, with Hotelling’s T2 control chart. Fusing these methods allows for controlling all upstream factors influencing multiple outcomes, summarised into a single control chart for streamlined monitoring. Our method advances the current frontier of predictive Statistical Process Control (SPC), facilitating multi-objective governance of manufacturing operations. This strategy notably simplifies the task of concurrently tracking numerous end-user attributes and their corresponding upstream factors. Empirical evidence demonstrates the capability of our methodology in predicting client-specific features and detecting early signals of perturbations in upstream process stability.