EconPapers    
Economics at your fingertips  
 

Digital twin for real-time data processing in logistics

Hendrik Haße, Bin Li, Norbert Weißenberg, Jan Cirullies and Boris Otto

A chapter in Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains, 2019, pp 4-28 from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management

Abstract: 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.

Keywords: Digital Twin; Real-time; KPI; IoT (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/209367/1/hicl-2019-27-004.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:hiclch:209367

Access Statistics for this chapter

More chapters in Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL) from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().

 
Page updated 2021-03-28
Handle: RePEc:zbw:hiclch:209367