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Title: Digital twin for real-time data processing in logistics
Language: English
Authors: Haße, Hendrik 
Li, Bin 
Weißenberg, Norbert 
Cirullies, Jan 
Otto, Boris 
Keywords: Digital Twin; Real-time; KPI; IoT
Issue Date: 26-Sep-2019
Publisher: epubli
Source: Hamburg International Conference of Logistics (HICL) 27: 3-28 (2019)
Abstract (english): 
Purpose: Key performance indicators (KPIs) are an essential management tool. Realtime KPIs for production and logistics form the basis for flexible and adaptive production systems. These indicators unfold their full potential if they are seamlessly integrated into the “Digital Twin” of a company for data analytics.
Methodology: We apply the Design Science Research Methodology for Information Systems Research for deriving a digital twin architecture.
Findings: Research in the field of digital twins is at an early state, where the main objective is to find new applications for this technology. The majority of digital twin applications relate to the fields of manufacturing. Finally, it became apparent that existing architectures are too generic for usage in logistics.
Originality: The approach presented is an affordable solution for stakeholders to start with a digital transformation, based on standards and therefore highly technology-independent. The combined use of a lambda architecture with a semantic layer for flexible KPI definition is a special case.
Conference: Hamburg International Conference of Logistics (HICL) 2019 
DOI: 10.15480/882.2462
ISBN: 978-3-750249-47-9
ISSN: 2365-5070
Journal: Proceedings of the Hamburg International Conference of Logistics (HICL) 
Document Type: Chapter/Article (Proceedings)
License: CC BY-SA 4.0 (Attribution-ShareAlike 4.0) CC BY-SA 4.0 (Attribution-ShareAlike 4.0)
Part of Series: Proceedings of the Hamburg International Conference of Logistics (HICL) 
Volume number: 27
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