This 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.
The 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.
The 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.
The 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.
A 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.
Al‐Tahat, M. and Rawabdeh, I. (2008), "Stochastic analysis and design of CONWIP controlled production systems", Journal of Manufacturing Technology Management, Vol. 19 No. 2, pp. 253-273. https://doi.org/10.1108/17410380810847945Download as .RIS
Emerald Group Publishing Limited
Copyright © 2008, Emerald Group Publishing Limited