Multi-Objective Economic-Statistical Design of VSSI-MEWMA-DWL Control Chart with Multiple Assignable Causes

Abstract

This paper proposes a multi-objective model for the economic-statistical design of the variable sample size and sampling interval multivariate exponentially weighted moving average control chart by using double warning lines. The Markov chain approach is used to obtain the statistical properties. We extend the Lorenzen and Vance cost function considering multiple assignable causes and multivariate Taguchi loss approach to obtain the expected cost per time unit. The meta-heuristic non-dominated sorting genetic algorithm is used to search for the Pareto optimal solutions. A numerical example is provided to illustrate the solution procedure. Finally, sensitivity analyses for some parameters are given.