Abstract
Choosing the most fitting manufacturing principle largely depends on the technical divisibility of jobs and the quantity to be produced. In most cases, a high quantity causes a higher degree of automation. What to do, however, if the production programme is evolving into various product modifications in the long run, thus developing from monolithic flow lines to a quasi-continuous batch production by means of bottleneck machines?
Classic push-controlled routines are failing here, since the batchwise manufacturing in combination with performance-reducing parameters within production systems will cause discontinuous outputs that are difficult to control and, moreover, feature an increased creation of work in process (WIP).
This problem is intensified by a combined influence of necessary setup activities, which often lead to sporadic machine failures. As a matter of fact, this invariably causes a dramatic delay in delivery times, not least because of the extension of the throughput times.
In this paper, we will introduce a manufacturing control that is based on dynamic WIP-oriented bottleneck planning, which will allow to maintain the automatically regulated output optimum by means of a self-controlling system.
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Wagenhaus, G., Gürke, N., Kurt, W., Bergmann, U. (2021). Dynamic Bottleneck Starvation Control. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-030-85914-5_58
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DOI: https://doi.org/10.1007/978-3-030-85914-5_58
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