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Standard stochastic models for supply chains predict the throughput time (TPT) of a part from a statistical distribution, which is dependent on the work in progress at the time the part enters the system. So they try to predict a transient response from data which are sampled in a quasi-steady-state situation. For reentrant supply chains this prediction is based on insufficient information, since subsequent arrivals can dramatically change the TPT. This paper extends these standard models by introducing the concept of a stochastic phase velocity which dynamically updates the TPT estimate. This leads to the concepts of temperature and diffusion in the corresponding kinetic and fluid models for supply chains.
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Armbruster et al. (2005) studied this question.
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