Multistage‐multiresponse models for dynamic quality chain design problems

Abstract

AbstractQuality of final products depends on several decision variables and design factors from several stages of operations. Multiresponse optimization is a well‐grounded method for offline quality design that can consider several inputs and outputs. This study introduces a new methodology for quality optimization in multistage systems with multiple response variables. Several stochastic parameters, including response surfaces and covariates, are to be considered in this methodology. For this purpose, scenario‐based multistage stochastic programming models are developed in three cases addressing (1) decision on control factors, (2) decision on control factors as well as targets of intermediate stages, and (3) scenario‐based decision on control factors. An example is presented at the end to illustrate the mechanism of the methodology and applicability of the three cases.