Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/228936 
Year of Publication: 
2020
Citation: 
[Editor:] Kersten, Wolfgang [Editor:] Blecker, Thorsten [Editor:] Ringle, Christian M. [Title:] Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29 [ISBN:] 978-3-7531-2346-2 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2020 [Pages:] 661-697
Publisher: 
epubli GmbH, Berlin
Abstract: 
Purpose: The purpose is to design a new concept for control of the Supply-Chain for the era of industry 4.0 exploiting the huge amount of actual data of material flow objects which are available thru new identification technologies, localization and communication systems and to use appropriate tools for evaluation and analyzing actual data. Methodology: The approach uses the idea of a Digital-Twin Concept for logistics that bases of three pillars: 1) 'reality': actual status of material flow objects 2) 'repository': digital mapping of material flow objects 3) 'regulation' of material flow. The real and virtual material flow objects are permanently compared, deviations are evaluated and harmonized by using the principle of closed-loop-control. Originality: The concept is a very new approach to master material flow for final products and required components. For this a 'Big- Picture' of a Digital Control Twin (DCT) System is designed, which is a necessary complement to the engineering oriented Digital-Twin-Concept to run a smart factory. Findings: The paper shows how the idea of a Digital Twin Concept for engineered products can be transferred into the world of logistics and especially for supply chains. The Digital Control Twin controls, monitors and balances material flow objects according to quantity, location and time and can help to predict and solve problems in advance.
Subjects: 
Logistics
Industry 4.0
Digitalization
Innovation
Supply Chain Management
Artificial Intelligence
Data Science
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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