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

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 disturba...

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Published inEURO Journal on Transportation and Logistics Vol. 7; no. 1; pp. 25 - 56
Main Authors Meyer, Anne, Sejdovic, Suad, Glock, Katharina, Bender, Matthias, Kleiner, Natalja, Riemer, Dominik
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Elsevier B.V 01.03.2018
Springer Berlin Heidelberg
Elsevier Limited
Subjects
Automobile industry
Automotive engineering
Automotive inbound networks
Business and Management
Complex event processing
Disruption
Errors
Logistics
Management Science
Online optimization
Operations Research
Operations Research/Decision Theory
Optimization
Real-time analytics
Research Paper
Transport and logistics
Transport processes
Online optimization
Transport and logistics
Automotive inbound networks
Real-time analytics
Complex event processing
Online AccessGet full text
ISSN2192-4376
2192-4384
2192-4384
DOI10.1007/s13676-017-0108-5

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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.
AbstractList 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.
Author Sejdovic, Suad
Kleiner, Natalja
Meyer, Anne
Glock, Katharina
Riemer, Dominik
Bender, Matthias
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CitedBy_id crossref_primary_10_1016_j_cirpj_2023_01_002
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Issue 1
Keywords Online optimization
Transport and logistics
Automotive inbound networks
Real-time analytics
Complex event processing
Language English
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SubjectTerms Automobile industry
Automotive engineering
Automotive inbound networks
Business and Management
Complex event processing
Disruption
Errors
Logistics
Management Science
Online optimization
Operations Research
Operations Research/Decision Theory
Optimization
Real-time analytics
Research Paper
Transport and logistics
Transport processes
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Title A disruption management system for automotive inbound networks: concepts and challenges
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