Compound-Estimator Based Cause-Selecting Control Chart for Monitoring Multistage Processes

Although there exists an increasing interest in monitoring and diagnosing multistage processes through the recent years, this issue has been overlooked to a large extent in cascade processes where the quality characteristics are liable to outliers. The presence of outliers has a debilitating effect on the detect-ability of the traditional cause selecting control charts and thus makes them unreliable. Therefore, the purpose of this article is to provide a robust approach to quality control in multistage processes. It is assumed that the process consists of two stages and the historical data with regard to both dependent quality characteristics contain outliers. A robust fitting procedure based on compound-estimator is employed to build the relationship between the quality variables and a robust monitoring approach is presented. Subsequently, simulation studies are undertaken to assess the performance of the robust scheme by means of the average run length (ARL) criterion. It is shown that the proposed robust procedure can much faster detect diverse types of shift.