Performance Evaluation Models for Single-Item Periodic Pull Production Systems

Abstract

A number of pull production systems reported in the literature are found to be equivalent to a tandemqueue so that existing accurate tandem-queue approximation methods can be used to evaluate such systems. In this study, we consider developing an exact performance evaluation model for a non-tandemqueue equivalent pull production system using discrete-time Markov processes. It is a periodically controlled serial production system in which a single-item is processed at each stage with an exponential processing time in order to satisfy the Poisson finished product demand. The selected performance measures are throughput, inventory levels, machine utilizations and service level of the system. For large systems, which are difficult to evaluate exactly because of large state-spaces involved, we also propose a computationally feasible approximate decomposition technique together with some numerical experimentations.

Analysis of a production system in a general configuration

“…Many researchers analyzed production systems with such a control strategy by queueing networks. Several decomposition approaches were proposed for evaluating performance measures (Kirkavak and Dincer [16], Frein and Di Mascolo [12], Di Mascolo [9], Di Mascolo et al [10], Mitra and Mitrani [17,18]). Deleersnyder et al [7] modeled a production system with the control strategy by a discrete time Markov process and proposed an iterative method for performance measures.…”