Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/209374 
Year of Publication: 
2019
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 27 [ISBN:] 978-3-7502-4947-9 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2019 [Pages:] 223-264
Publisher: 
epubli GmbH, Berlin
Abstract: 
Purpose: Shuttle based storage and retrieval systems (SBS/RS) are suitable for applications which require a high throughput. Many times, however, the maximum performance of SBS/RS is not required. For example, when customers initiate a large number of retrieval requests at a specific time, or when a large number of storage requests enter the system at fixed times due to scheduled inbound deliveries. This article presents and discusses an algorithm that is based on closed-loop-control. Methodology: A situation-dependent adaptation of the velocity to the currently required throughput or the number of currently awaiting orders requires an algorithm which needs to be implemented in the control of the SBS/RS. A simulation model of a SBS/RS will be introduced, which contains the control of the shuttle carriers and elevators as well as a model for calculating the energy requirement. Findings: The results of this paper is the quantified energy saving by the application of the algorithm for situation-dependent adaption of velocity for SBS/RS Originality: To our knowledge this is the first paper that introduces a situation-dependent adaption of velocity for SBS/RS.
Subjects: 
Shuttle based systems
Simulation
Energy consumption
Velocity adaption
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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