Transient analysis of manufacturing systems performance

Abstract

Studies in performance evaluation of automated manufacturing systems, using simulation or analytical models, have always emphasized steady-state or equilibrium performance in preference to transient performance. In this study, we present several situations in manufacturing systems where transient analysis is very important. Manufacturing systems and models in which such situations arise include: systems with failure states and deadlocks, unstable queueing systems, and systems with fluctuating or nonstationary workloads. Even in systems where equilibrium exists, transient analysis is important in studying issues such as accumulated performance rewards over finite intervals, first passage times, sensitivity analysis, settling time computation, and deriving the behavior of queueing models as they approach equilibrium. In this paper, we focus on transient analysis of Markovian models of manufacturing systems. After presenting several illustrative manufacturing situations where transient analysis has significance, we discuss two problems for demonstrating the importance of transient analysis. The first problem is concerned with the computation of distribution of time to absorption in Markov models of manufacturing systems with deadlocks or failures, and the second problem shows the relevance of transient analysis to a multiclass manufacturing system with significant setup times. We also discuss briefly computational aspects of transient analysis.