Cyber-Physical Systems for Performance Monitoring in Production Intralogistics

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The realization of a higher business value in manufacturing requires optimized internal logistics systems in terms of operational performance, uptime and sustainability. This paper deals with the introduction of Internet of Things (IoT) to unlock new capabilities for enhancing the performance of intralogistics. Specifically, it introduces a design perspective for IoT-driven analytics in intralogistics, within a Cyber-Physical Systems (CPS) approach. Such an approach enables the creation of data process chains linked to performance measurement for intralogistics, a prerequisite for optimizing logistics operations within production environments. An overview of key performance indicators for this domain is offered, followed by an outline of recent research on IoT and CPS and the role of context information management for IoT-enabled data process chains. The conceptual model is illustrated through a representative use case of a CPS demonstrator for performance monitoring in intralogistics. The application implements a simple data process chain, starting from the acquisition and processing of data from a conveyor testbed, followed by the determination and visualization of appropriate performance monitoring information on a dashboard.
Translated title of the contributionCyberphysikalische Systeme zur Leistungsüberwachung in der Produktionsintralogistik
Original languageEnglish
Article number106333
Number of pages25
JournalComputers & Industrial Engineering
Volume142
DOIs
Publication statusPublished - 1 Feb 2020

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Monitoring
Logistics
Testbeds
Information management
Sustainable development
Visualization
Cyber Physical System
Internet of things
Processing
Industry

Keywords

    Fields of Expertise

    • Mobility & Production

    Cite this

    Cyber-Physical Systems for Performance Monitoring in Production Intralogistics. / Mörth, Oliver; Emmanouilidis, Christos; Hafner, Norbert; Schadler, Michael.

    In: Computers & Industrial Engineering, Vol. 142, 106333, 01.02.2020.

    Research output: Contribution to journalArticleResearchpeer-review

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