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A disruption management system for automotive inbound networks: concepts and challenges
Author(s) -
Anne Meyer,
Suad Sejdovic,
Katharina Glock,
Matthias Bender,
Natalja Kleiner,
Dominik Riemer
Publication year - 2017
Publication title -
euro journal on transportation and logistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.433
H-Index - 20
eISSN - 2192-4384
pISSN - 2192-4376
DOI - 10.1007/s13676-017-0108-5
Subject(s) - automotive industry , transparency (behavior) , production (economics) , risk analysis (engineering) , computer science , lean manufacturing , process management , field (mathematics) , systems engineering , business , manufacturing engineering , engineering , computer security , macroeconomics , mathematics , pure mathematics , economics , aerospace engineering
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.

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