Estimating process batch flow times in a two-stage stochastic lowshop with overlapping operations
This paper focuses on modelling the impact of lot splitting on average process batch flow times, in a two-stage stochastic flowshop. It is shown that the traditional queueing methodology for estimating flow times cannot be directly applied to a system with lot splitting, as the arrival process of sublots at the second stage is not a renewal process. Consequently, an embedded queueing model is developed in order to approximate the average flow time of the flags through the system; from the flow time of the flags, the flow time of process batches can then be derived. The model turns out to yield very satisfactory results, and provides a tool to quantify the reduction in flow time that can be obtained by overlapping operations at different processing stages. Moreover, it allows to model the trade-off between flow time improvement and gap time occurrence by using it within the scope of a cost model.
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