Abstract
The corresponding author worked for many years with Toyota coaches, supporting Bosch in the development of pilot value streams for the Bosch Production system. The coaches spent considerable time and effort to analyze and decouple production from customer fluctuations and to stabilize the flow of production with adequate inventory buffers and capacity. The project team, on the other hand, was impatient, wanting to redesign lines, install Kanban and perform Kaizen activities. They did not understand that their coach was reducing unevenness and overload, so called Mura and Muri, striving for basic stability, as a precondition for lean activities. Later, they denoted a line possessing this basic stability in Bosch as an “improvable system”. In this paper the authors develop methods to analyze and reduce variability in value streams. The value stream is divided into zones, which are then qualified as stable or unstable. Measures are introduced to turn unstable into stable zones, step by step, enabling sustainable improvement activities in those stabilized zones. An IT system is developed to acquire and process the vast amount of data needed for variability measurements, and to provide structured information to support the management of variability in production.
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Richter, R., Deuse, J., Willats, P., Syberg, M., Lenze, D. (2021). Managing Variability in Production. 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 630. Springer, Cham. https://doi.org/10.1007/978-3-030-85874-2_80
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