Transient Analysis of Manufacturing System Performance

Studies in performance evaluation of automated manufacturing systems, us. ing 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 non-stationary 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 certain systems, convergence to steady-state is so slow that only transient analysis can throw light on the system performance. After presenting several illustrative manufacturing situations where transient analysis has significance, we discuss two applications: (1) computation of distribution of time to absorption in Markov models of manufacturing systems with deadlocks or failures, and (2) computation of distribution of manufacturing cycle time in a failure-prone manufacturing system operated over a finite shift period. We also briefly discuss computational aspects of transient analysis.