Stochastic analysis and design of CONWIP controlled production systems

Abstract

PurposeThis paper aims to present a model of a multi‐phase multi‐product manufacturing system considering a CONstant work‐in‐process (CONWIP) control mechanism and using continuous‐time Markov chain modelling approach.Design/methodology/approachThe model includes defining a state space then constructing the rate matrix, which contains the transition rates, followed by formulating the transition matrix. The time‐dependent probabilities that a product is in a particular state at a certain time are characterized. Performance measures related to the statistics on the waiting time and average number of work‐in‐process in the production system have been determined. Consequently, a numerical example is presented to illustrate the computations of different model aspects.FindingsThe analyses explain a foundation needed for analyzing the steady state behavior of manufacturing systems. Results have shown how production data can be easily modified for what‐if analyses by the use of Excel add‐in tool.Practical implicationsThe multi‐level model outlines a framework that provides a practical tool for production engineers seeking to enhance the performance of their production system by selecting the best order release mechanism.Originality/valueA novel aspect of the work reported in this paper is the application of Chapman‐Kolmogrov mathematics and CONWIP ordering theory, which is developed for evaluating and managing CONWIP controlled production systems.