On process monitoring using location control charts under different loss functions

Abstract

Process monitoring is essential and plays a vital role in enhancing the quality of the output. For this purpose, many statistical tools are used in practice and the control chart is one of the most popular choices. Bayesian and classical set-ups are two major and popular categories for defining the design structures of different types of control charts. This study planned to investigate the Bayesian control charts under different loss functions to ensure an efficient monitoring of process parameters for quality control. The performance measures used in this study are average run length (ARL), relative ARL (RARL), extra quadratic loss (EQL) and performance comparison index (PCI). It has been observed that the application of Bayesian structure of process monitoring needs careful consideration in terms of prior distribution, sampling and posterior (predictive) distributions, and the choice of loss functions, in order to obtain reliable outcomes.

Keywords

ARL EQL hyperparameters loss functions PCI power predictive distribution process monitoring RARL

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