Determining some of the triggers for early life cycle failure in decay affected logistic queueing simulation

Abstract

Life-cycle cost estimates for large scale, long term, future military capabilities are difficult to make and subject to complexities. Usually they are generated from anecdotal experience. However, experience may not be a sound basis, so modelling and simulation are employed to define conditions that lead to early system failure in measures such as availability levels or the capability's life-of-type. Such models typically have common characteristics, including decay or degradation, queueing delays, availability of resources, and maintenance processes. Our generic model is a queue server, discrete event simulation that emulates macroscopic maintenance processes using time based parameters and statistical distributions. Previously we reported that the simulated system shows evidence of bifurcation-like behaviour in life-of-type estimates. This suggested that uncertainties in microscopic variables (such as inter-arrival times) cause instabilities in high level strategic performance indicators, making the prediction of such indicators difficult and bringing into question the use of mean based estimation methods for inventory provisioning. Our objective is to define the conditions which lead to system failure. We use a series of numerical simulation experiments to investigate and define such conditions. Outcomes show that system performance is sensitive to the types of input distribution used and that decay processes are strongly associated with complex behaviour even when most of the interacting factors of the real system have been removed from the simulation. References

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