On the Validity of Approximation Formulae for Machine Downtimes

In this paper we investigate how simplifying assumptions in the stochastic modeling of machine downtimes affect the output performance measures. Typically, literature in this area either addresses the estimation of statistical input modeling as such or investigates how sensitive output performance measures of queueing or simulation models are to the choice of stochastic properties of the input distributions. Practitioners, however, often prefer to use simplified formulae for a rough-cut analysis. The results presented clearly show, that unjustified simplification might lead to erroneous results. The immediate conclusion out of the results is that sampling shop-floor data should not only include first order statistics, but also measures that allow to monitor and model the variability of the machinery.