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A disruption management system for automotive inbound networks: concepts and challenges

Meyer, Anne ORCID iD icon; Sejdovic, Suad; Glock, Katharina; Bender, Matthias; Kleiner, Natalja; Riemer, Dominik

Abstract:

Production processes in the automotive industry are highly dependent on reliable inbound logistics processes, because in lean production systems delays or mistakes often result in expensive interruptions of production processes. However, transport processes are always subject to unavoidable disturbances, delays, or mistakes. The goal of the research project ProveIT is to provide an IT system improving the transparency by monitoring transport processes in real-time: deviations from the transport plans are identified predictively, and classified dynamically as disruptions if they have negative impacts on the subsequent processes. If a disruption occurs, the operations managers are provided with mitigation actions automatically generated by escalation-based online optimization algorithms. In this contribution, we introduce the use cases, the architecture and main concepts of the ProveIT disruption management system, and report on challenges faced during field experiments with our application partners, Bosch, ZF, and Geis.


Verlagsausgabe §
DOI: 10.5445/IR/1000164428
Veröffentlicht am 15.11.2023
Originalveröffentlichung
DOI: 10.1007/s13676-017-0108-5
Scopus
Zitationen: 4
Dimensions
Zitationen: 6
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationsmanagement im Ingenieurwesen (IMI)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 03.2018
Sprache Englisch
Identifikator ISSN: 2192-4376
KITopen-ID: 1000164428
Erschienen in EURO Journal on Transportation and Logistics
Verlag Springer
Band 7
Heft 1
Seiten 25–56
Schlagwörter Real-time analytics, Complex event processing, Online optimization, Transport and logistics, Automotive inbound networks
Nachgewiesen in Dimensions
Scopus
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