Towards logistics 4.0: an edge-cloud software framework for big data analytics in logistics processes

Moritz von Stietencron, Karl Hribernik, Katerina Lepenioti, Alexandros Bousdekis, Marco Lewandowski, Dimitris Apostolou and Gregoris Mentzas

International Journal of Production Research, 2022, vol. 60, issue 19, 5994-6012

Abstract: Logistics 4.0 aims at enabling the sustainable satisfaction of customer demands with optimised costs of services with the use of emerging technologies, such as Internet of Things, streaming analytics, and optimised decision making. The availability of massive sensor data streams over time opens new perspectives for extracting meaningful and timely insights from data-in-motion through streaming analytics. Logistics 4.0 is a relatively new field of research which demands the development of scalable and efficient software solutions and their deployment to successful real-life case studies. In this paper, we propose a software framework for streaming analytics in an edge-cloud computational environment aiming at covering the whole data analytics lifecycle in logistics processes and thus, advancing the evolution and realisation of the Logistics 4.0 concept. The proposed framework takes advantage of edge computing technologies, streaming analytics and proactive decision making in order to monitor, analyse and support decision making in the frame of Logistics 4.0. It is applied and evaluated in a maintenance service logistics use case from the aerospace industry.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2021.1977408 (text/html)
Access to full text is restricted to subscribers.

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:taf:tprsxx:v:60:y:2022:i:19:p:5994-6012

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2021.1977408

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().