Abstract
Simulation models are still often only part for decision support in the planning area. For short-term decisions at the operational level, there have been good fundamentals since the 1990s, but still relatively few implementations, especially in the logistics sector. Our approach is to use real-time data to provide short-term forecasts, by using a simulation model that provides required information. Due to current hardware and a well-chosen degree of abstraction of the model, real-time decision support (“real-time” means in this context: fast enough to support the decision) is possible. This paper presents a concept of a procedure model for the realization of such operational simulation-based decision support, applied to the picking area of an industrial laundry. The operational use of the simulation model is part of the project “Laundry Order Consolidation System (LOCSys)”, which aims to improve the picking & storing processes in the clean area of an industrial laundry through automation.
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Acknowledgements
As part of the “Zentrales Innovationsprogramm Mittelstand” (ZIM; central innovation program), the Federal Ministry for Economic Affairs and Energy of Germany launched a research and development project to find an innovative solution for automating the picking area in industrial laundries. The project is called “LOCSys—Laundry Order Consolidation System”. Part of LOCSys is the use of an operational simulation model to provide short-term forecasts and support the decision-making of the automated picking system.
We are very thankful for the financial support of the ministry, which allows us to research for new picking solutions in the laundry industry.
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Müller, M., Reggelin, T., Schmidt, S. (2019). Operational Simulation-Based Decision Support in Intralogistics Using Short-Term Forecasts. In: Kabashkin, I., Yatskiv (Jackiva), I., Prentkovskis, O. (eds) Reliability and Statistics in Transportation and Communication. RelStat 2018. Lecture Notes in Networks and Systems, vol 68. Springer, Cham. https://doi.org/10.1007/978-3-030-12450-2_33
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