Pooling in manufacturing: do opposites attract?

In a stochastic environment pooling naturally leads to economies of scale, but heterogeneity can also create variability. In this article, we investigate this trade-off in the case of a manufacturing environment. Pooling for queueing systems has been widely investigated while much less attention has been given to manufacturing systems where jobs are given a due date upon arrival. In such system it is not the elapsed time until the actual completion of the job that counts, but rather the lead time that can be promised to the customer in order to guarantee a high service level. In this paper, we study the benefits of pooling stochastic systems in such manufacturing setting with multiple customer types. Our results demonstrate that, in stark contrast with what was previously observed in service environments, heterogeneity is generally not deteriorating performance. Furthermore, our analytical and simulation studies reveal that the benefits of pooling in terms of the expected sojourn time can serve as a good prediction for the benefits of pooling on the average due-date lead time in a wide range of situations.

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