A progressive approach to joint monitoring of process parameters

Abstract Process monitoring is a continuous phenomenon and it needs careful attention for an improved quality of output. Location and dispersion parameters play a vital role in regulating every process and it requires a timely detection of any change in their stable behaviors. Nowadays, practitioners prefer a single charting setup that offers better ability to detect joint shifts in the process parameters. In this study, we propose a new parametric memory-type charting structure based on progressive mean under max statistic, namely Max-P chart, for the joint monitoring of location and dispersion parameters. Assuming normality of the quality characteristics of interest this study provides an extensive comparison between the proposed chart and some existing schemes for joint monitoring of process location and dispersion parameters. We use run length properties for the performance analysis of different schemes under investigation in this study. These properties include individual and overall measures (average run length, standard deviation run length, extra quadratic loss, relative average run length, and performance comparison index) for comparative analysis. The study findings reveal that the newly proposed Max-P monitoring scheme offers relatively better performance to detect shifts in the process parameter(s). A real-life application of is also included from electrical engineering where the monitoring of the voltage of photovoltaic system is desired. The proposed scheme also offers better detection ability to identify special causes in the parameters of electrical process.