Adaptive EWMA-S² control charts with adaptive smoothing parameter

Abstract

Memory charts like EWMA-S² or CUSUM-S² are designed to detect a particular change in the process variance efficiently. However, the charts could be inefficient to detect some other shifts. To overcome this constraint, control charts with adaptive schemes that are efficient for a wide range of shifts can be used. This work proposes new adaptive EWMA charts for the dispersion (AEWMA-S²) based on an adaptive smoothing parameter that relates its value to the potential shift of the process. A Markov chain approach is used to optimize its design. A simulation experiment shows the advantage of the proposed charts.

Keywords:

• Adaptive control charts
• average run length
• EWMA
• CUSUM
• statistical process control

Acknowledgments

We are very grateful to the referees and the editor for their constructive comments and suggestions, which have led to an improved version of the article.

Additional information

Funding

This research has received financial support from the government of Peru, under contract 49-2018 of the project “Proyecto de Mejoramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia, Tecnología e Innovación Tecnológica 8682PE”, of CONCYTEC/FONDECYT/World Bank Group.