On efficient construction and evaluation of runs rules–based control chart for known and unknown parameters under different distributions

Abstract

Abstract In this study, we have considered two design structures of control chart by covering the situations of known and unknown parameters, variety of probability distributions, and runs rules. The design structures are dependent on constants which generally considered hard to compute analytically. For construction of constants and also for evaluating performance of the design structures through performance measures, we have illustrated Monte Carlo simulation procedure/algorithm for researcher and practitioners. Furthermore, based on the Monte Carlo simulation procedures, we have established a program in R language to compute values of different constants and performance measures. Results illustrated that design structures for known and unknown parameters under variety of runs rules and probability distributions have outstanding performance in contrast to existing structures. Moreover, design structure for unknown parameters behaves alike the design structure for known parameters. This indicates that design structure for unknown parameters has the ability to resolve the issue of runs rules which generally occur when parameters are estimated. Besides, two real‐life examples have been included in which physicochemical characteristic of groundwater and plasticizer characteristic of petrochemical process are monitored through design structures.

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