A Novel Simulation-Based Adaptive MEWMA Approach for Monitoring Linear and Logistic Profiles

As a common approach in the development of control charts Statistical Process Control (SPC), an industrial process is monitored with one or more quality characteristics using their corresponding distributions. Note though, modelling through relation between some independent and dependent variables alternative which designated as profiles monitoring. This study proposes integration adaptive to conventional Multivariate Exponentially Weighted Moving Average (MEWMA) chart improve its detection ability phase II application. The run length MEWMA are measured use Monte Carlo simulations by better performance proposed method than numerous existing competitors including indicated monitoring linear logistic profiles. Finally, real-life example from semiconductor manufacturing provided demonstrate implementation superiority over chart.