Improved Design of Proportional Integral Derivative Charts

Abstract

Jiang et al. (2002) introduced proportional integral derivative (PID) control charts for monitoring autocorrelated processes based on PID predictors and corresponding residuals. The major contribution of the PID chart is to bridge between engineering process control (EPC) techniques and statistical process control (SPC) schemes. Although the performance of PID charts has been reported in the literature, we focus on several design issues of this control scheme. In this paper, we consider the PID charting parameter design, the mean-shift pattern analysis, and the relationship between the average run-length (ARL) performance and PID parameter selection. Improved design schemes are suggested for different scenarios of autocorrelated processes and verified with Monte Carlo simulation.

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