J. C. Arlinghaus
Prof. Dr. oec. Julia Arlinghaus
Chair of Production Systems and Automation
Beruflicher Werdegang
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10/2019–present |
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Director, Fraunhofer-Institut für Fabrikbetrieb und -automatisierung IFF Magdeburg |
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10/2019–present |
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Chair of the Department of Production Systems and Automation, Otto von Guericke University Magdeburg |
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8/2017–9/2019 |
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W3 Professor of the Management of Industrie 4.0 / Management of Digitalization and Automation, RWTH Aachen |
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5/2013–7/2017 |
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Associate Professor of Network Optimization in Production and Logistics, Adjunct Professor since 8/2017, Jacobs University Bremen |
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1/2012–3/2013 |
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Consultant, Porsche Consulting GmbH, Bietigheim-Bissingen |
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9/2008–11/2011 |
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Graduate assistant, University of St. Gallen, Switzerland |
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1/2005–8/2008 |
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Research associate and project manager, Bundesvereinigung für Logistik (BVL), Bremen |
Education
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9/2008–9/2011 |
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Doctorate in economics finance, University of St. Gallen |
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10/2002–11/2007 |
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Diplom degree in engineering management, University of Bremen |
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3/2007–7/2007 |
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DAAD grant, Research into Artifacts Center for Engineering (RACE), Tokyo University, Japan |
Professional Memberships
| since 10/2024 |
acatech - Deutsche Akademie der Technikwissenschaften - Member |
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| since 09/2024 |
Wissenschaftliche Gesellschaft für Arbeits- und Betriebsorganisation (WGAB) e.V. - Member |
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| since 02/2024 |
Wissenschaftsrat der Bundesregierung - Chairwoman of the Scientific Commission |
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| since 01/2023 |
Forschungsbeirat Industrie 4.0 - Mitglied |
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| since 08/2022 |
High-Tech Gründerfonds (HTGF) Invest Comitee Industrial Tech - Member |
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since 10/2021 |
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Bundesvereinigung Logistik - Member of the Scientific Advisory Board |
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since 06/2021 |
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Industrieausschuss IHK Magdeburg - Member |
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since 04/2021 |
Daimler und Benz Stiftung - Member of the Board |
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since 02/2021 |
Wissenschaftsrat der Bundesregierung -Member |
2025
Peer-reviewed journal article
Dynamic multi-period recycling collection routing with uncertain material quality
Cuellar-Usaquén, Daniel; Ulmer, Marlin W.; Antons, Oliver; Arlinghaus, Julia C.
In: OR spectrum - Berlin : Springer . - 2025, insges. 44 S. [Online first]
2024
Book chapter
Motion Capture-Technologien für die Ergonomie-Analyse - ein Review
Harnau, Erik; Arlinghaus, Julia; Breiter, Stephan
In: Arbeitswissenschaft in-the-loop: Mensch-Technologie-Integration und ihre Auswirkung auf Mensch, Arbeit und Arbeitsgestaltung / Gesellschaft für Arbeitswissenschaft , 2024 - Sankt Augustin : GfA-Press, Artikel J.1.6, insges. 6 S.
Subskriptions-Ökosysteme im industriellen Kontext - wie können Partner bei der Bewältigung von Schlüsselherausforderungen in der Umsetzung von Abo-Modellen unterstützen?
Burger, Markus; Burgmann, Nils; Krüger, Andreas; Arlinghaus, Julia C.
In: Digitale Plattformen und Ökosysteme im B2B-Bereich - Wiesbaden : Springer Fachmedien Wiesbaden ; Schallmo, Daniel *1978-* . - 2024, S. 183-208, 1 Online-Ressource [Literaturverzeichnis: Seite 204-206]
A case stucy on technology selection and didactical design for immersive learning and dialog spaces
Haase, Tina; Ha Claudia Vuong, Thu; Arlinghaus, Julia C.
In: Training, education and learning science - New York : AHFE Open Access ; Nazir, Salman . - 2024, S. 11-17 [Konferenz: 15th International Conference on Human Factors and Ergonomics and the Affiliated Conference, Nice, France, July 24-27, 2024]
Perception of biases in machine learning in production research
Götte, Gesa; Antons, Oliver; Herzog, Andreas; Arlinghaus, Julia C.
In: Workshop Proceedings "AI in Production" - Leipzig : Hochschule für Technik, Wirtschaft und Kultur Leipzig ; Krockert, Martin . - 2024, insges. 11 S.
Comparing digital twins and virtual engineering in buyer supplier relationships for complex production facilities
Janecki, Luca; Antons, Oliver; Reh, Daniel; Arlinghaus, Julia C.
In: Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments , 1st ed. 2024. - Cham : Springer Nature Switzerland ; Thürer, Matthias, S. 180-193 - (IFIP Advances in Information and Communication Technology; 733) [Konferenz: 43rd IFIP WG 5.7 International Conference, APMS 2024, Chemnitz, Germany, September 8-12, 2024]
A literature review on the cross-domain usage of digital factory twins within design time
Schröder, Adrian; Antons, Oliver; Arlinghaus, Julia C.
In: Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments , 1st ed. 2024. - Cham : Springer Nature Switzerland ; Thürer, Matthias, S. 315-329 - (IFIP Advances in Information and Communication Technology; 730) [Konferenz: 43rd IFIP WG 5.7 International Conference, APMS 2024, Chemnitz, Germany, September 8-12, 2024]
Artificial intelligence meets serious gaming
Freese, Maria; Zürn, Birgit; Arlinghaus, Julia C.
In: GI-Edition. Proceedings / Gesellschaft für Informatik - Bonn : Ges. für Informatik, Bd. P337 (2024), S. 437-438 [Workshop: INFORMATIK 2023, Berlin, 26.-29. September 2023]
Approaching cognitive biases in the circular economy through serious gaming
Behnert, Anna-Kristin; Arlinghaus, Julia C.; Kessler, Melanie; Freese, Maria
In: Human Factors, Business Management and Society - New York, NY : AHFE Open Access ; Salminen, Vesa . - 2024, S. 11-21 - (AHFE international; volume 135) [Konferenz: 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, Nice, France, 24-27 July 2024]
Planung und Steuerung für die digitale Produktion
Arlinghaus, Julia C.; Antons, Oliver
In: Handbuch Unternehmensorganisation , Living reference work, continuously updated edition - Wiesbaden : Springer Fachmedien ; Spath, Dieter *1952-* . - 2016, insges. 12 S.
Designing hybrid intelligence - understanding the impact of human decision-making on AI
Kessler, Melanie; Antons, Oliver; Arlinghaus, Julia C.
In: Advances in Manufacturing, Production Management and Process Control - New York : AHFE Open Access ; Mrugalska, Beata . - 2024, S. 31-39 [Konferenz: 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, Nice, France, 24-27 July 2024]
Peer-reviewed journal article
Digitale transformation and serious gaming - identifying success factors for smart factories
Freese, Maria; Kessler, Melanie; Arlinghaus, Julia C.; Maaß, Eike
In: Industry 4.0 Science , [Englische Ausgabe] - Berlin, Germany : GITO mbH, Bd. 40 (2024), Heft 5, S. 114-121
Motion-Capture-Systeme in der menschzentrierten Industrie 5.0
Harnau, Erik; Arlinghaus, Julia C.
In: Factory Innovation - Berlin : GITO mbH - Verlag für Industrielle Informationstechnik und Organisation . - 2024
Automated disassembly of e-waste - requirements on modeling of processes and product states
Saenz, José; Felsch, Torsten; Walter, Christoph; König, Tim; Poenicke, Olaf; Bayrhammer, Eric; Vorbröcker, Mathias; Berndt, Dirk; Elkmann, Norbert; Arlinghaus, Julia
In: Frontiers in robotics and AI - Lausanne : [Verlag nicht ermittelbar], Bd. 11 (2024), Artikel 1303279, insges. 20 S.
Interactions between planners’ and PPC systems - derivation of simulation scenarios with consideration of cognitive bias and disruptions
Rannertshauser, Patrick; Antons, Oliver; Arlinghaus, Julia
In: Procedia computer science - Amsterdam [u.a.] : Elsevier, Bd. 232 (2024), S. 1367-1376
Selection of motion capture technologies for Industry 5.0 production systems - a structured literature review
Harnau, Erik; Breiter, Stephan; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 58 (2024), Heft 19, S. 970-975
Characterizing circular and open business models in a profit-driven environment through business model patterns
Behnert, Anna-Kristin; Antons, Oliver; Arlinghaus, Julia C.
In: Procedia computer science - Amsterdam [u.a.] : Elsevier, Bd. 232 (2024), S. 436-445
Framework conditions for the transformation toward a sustainable carbon-based chemical industry - a critical review of existing and potential contributions from the social sciences
Matthies, Ellen; Beer, Katrin; Böcher, Michael; Sundmacher, Kai; König-Mattern, Laura; Arlinghaus, Julia C.; Blöbaum, Anke; Jaeger-Erben, Melanie; Schmidt, Karolin
In: Journal of cleaner production - Amsterdam [u.a.] : Elsevier Science, Bd. 470 (2024), Artikel 143279, insges. 13 S.
Digitale Transformation und Serious Gaming - Erfolgsfaktoren für intelligente Fabriken
Freese, Maria; Kessler, Melanie; Arlinghaus, Julia C.; Maaß, Eike
In: Industry 4.0 Science - Berlin : GITO mbH Verlag für Industrielle Informationstechnik und Organisation, Bd. 40 (2024), Heft 5, S. 114-121
Digital twins and their implications for business models - overview and potentials
Adelsberger, Rodrigo Torres; Antons, Oliver; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 58 (2024), Heft 19, S. 409-414
Exploring the challenges of circular economy adoption - a supply chain perspective
Behnert, Anna-Kristin; Antons, Oliver; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 58 (2024), Heft 19, S. 211-216
Non-peer-reviewed journal article
Overcoming heuristics that hinder people's acceptance of climatechange-mitigation technologies
Blöbaum, Anke; Schmidt, Karolin; Böcher, Michael; Arlinghaus, Julia C.; Kraus, Frederike; Matthies, Ellen
In: Charlottesville, VA: Center for Open Science, 2024, 1 Online-Ressource - (OSF preprints)
Dynamic multi-period recycling collection routing with uncertain meterial quality
Cuellar-Usaquén, Daniel; Ulmer, Marlin Wolf; Antons, Oliver; Arlinghaus, Julia C.
In: Magdeburg: Otto-von-Guericke-Universität Magdeburg: Fakultät für Wirtschaftswissenschaft, 2024, 1 Online-Ressource (37 Seiten, 0,9 MB) - (Working paper series; Otto von Guericke Universität Magdeburg, Faculty of Economics and Management; 2024, no. 1)
2023
Abstract
Nachweis psychischer Beanspruchung bei Stressreaktionen im Arbeitsumfeld durch objektive und subjektive Messverfahren
Steigemann, Lea Marie; Wagner, L. M.; Cholewinski, D.; Haase, Tina; Fachet, Melanie; Böckelmann, Irina; Darius, Sabine; Arlinghaus, Julia C.; Hoeschen, Christoph
In: 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Physik, DGMP 2023 / Deutsche Gesellschaft für Medizinische Physik , 2023 - [Berlin] : [Deutsche Gesellschaft für Medizinische Physik e.V.], S. 166-167, Artikel PS03.09 [Konferenz: 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Physik, DGMP 2023, Magdeburg, 27.-30.09. 2023]
Just in time vs. all in sync: an analysis of two types of synchronization in a minimal model of machine activity in industrial production based on excitable dynamics on graphs
Bose, Sanghita; Lesne, Annick; Arlinghaus, Julia C.; Hütt, Marc-Thorsten
In: Verhandlungen der Deutschen Physikalischen Gesellschaft / Deutsche Physikalische Gesellschaft - Bad Honnef : DPG . - 2023, Artikel SOE 4.3 [Tagung: DPG-Frühjahrstagung der Sektion Kondensierte Materie, SKM, Dresden, 26.-31.03.2023]
Atemgasanalyse zur Beurteilung und Erfassung von psychischer Beanspruchung bei Stressreaktionen im Arbeitsumfeld
Fachet, Melanie; Haase, Tina; Steigemann, Lea-Marie; Wagner, Leonie Marlene; Cholewinski, D.; Darius, Sabine; Böckelmann, Irina; Arlinghaus, Julia C.; Hoeschen, Christoph
In: 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Physik, DGMP 2023 / Deutsche Gesellschaft für Medizinische Physik , 2023 - [Berlin] : [Deutsche Gesellschaft für Medizinische Physik e.V.], S. 350-351, Artikel AS16.04 [Konferenz: 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Physik, DGMP 2023, Magdeburg, 27.-30.09. 2023]
Book chapter
Frugal innovation and sustainability - bringing together polarized views from the state of the art
Knizkov, Stephanie; Arlinghaus, Julia
In: Handbook on frugal innovation - Cheltenham, UK : Edward Elgar Publishing ; Leliveld, André *1962-* . - 2023, S. 84-101
Sustainability in chemical production - multi-objective distributed control
Antons, Oliver; Benecke, Tobias; Mostaghim, Sanaz; Arlinghaus, Julia C.
In: New trends in intelligent software methodologies, tools and techniques - Amsterdam : IOS Press, Incorporated ; Fujita, Hamido . - 2023, S. 211-219 [Konferenz: 22nd International Conference on New Trends in Intelligent Software Methodology, Tools, and Techniques, SoMeT_23, Naples, Italy, 22-23 September 2023]
A coevolution approach for the multi-objective dircular supply chain problem
Benecke, Tobias; Antons, Oliver; Mostaghim, Sanaz; Arlinghaus, Julia C.
In: IEEE CAI 2023 / IEEE Conference on Artificial Intelligence , 2023 - Los Alamitos : IEEE, S. 222-223 [Konferenz: 2023 IEEE Conference on Artificial Intelligence, CAI 2023, Santa Clara, Califonien, USA, 05-06 June 2023]
Productive teaming under uncertainty: when a human and a machine classify objects together
Rother, Anne; Notni, Gunther; Hasse, Alexander; Noack, Benjamin; Beyer, Christian; Reißmann, Jan; Zhang, Chen; Ragni, Marco; Arlinghaus, Julia C.; Spiliopoulou, Myra
In: 2023 IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO) , 2023 - [Piscataway, NJ] : IEEE, S. 9-14
A generalized circular supply chain problem for multi-objective evolutionary algorithms
Benecke, Tobias; Antons, Oliver; Mostaghim, Sanaz; Arlinghaus, Julia C.
In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation - New York, NY, United States : Association for Computing Machinery . - 2023, S. 355-358 [Konferenz: Companion Conference on Genetic and Evolutionary Computation, GECCO '23 Companion, Lisbon, Portugal, July 15 - 19, 2023]
Peer-reviewed journal article
Designing distributed decision-making authorities for smart factories - understanding the role of manufacturing network architecture
Antons, Oliver; Arlinghaus, Julia C.
In: International journal of production research - London [u.a.] : Taylor & Francis . - 2023, insges. 19 S. [Online first]
Risikomanagement 4.0 in der digitalisierten Fabrik
Kessler, Melanie; Arlinghaus, Julia C.
In: Controlling - München : Beck, Bd. 35 (2023), Heft Spezialausgabe, S. 55-69
Hybrid intelligence in procurement - disillusionment with AI’s superiority?
Burger, Markus; Nitsche, Anna-Maria; Arlinghaus, Julia C.
In: Computers in industry - Amsterdam [u.a.] : Elsevier Science, Bd. 150 (2023), Artikel 103946
Risk management behaviour in digital factories - the influence of technology and task uncertainty on managerial risk responses
Keßler, Melanie; Rosca, Eugenia; Arlinghaus, Julia C.
In: Supply chain management - Bingley : Emerald . - 2023 [Online first]
Open source as an enabler for circularity: A systematic literature review
Behnert, Anna-Kristin; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 120 (2023), S. 75-80
Maximum likelihood and neural network estimators for distributed production control
Antons, Oliver; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 56 (2023), Heft 2, S. 10327-10332
Autonomous vehicles as self-driving assembly items - functional requirements and ramifications for assembly sequences, automotive design and performance
Kathmann, Tom; Reh, Daniel; Arlinghaus, Julia C.
In: Journal of manufacturing systems - Amsterdam [u.a.] : Elsevier Science, Bd. 70 (2023), S. 327-344
Exploiting the technological capabilities of autonomous vehicles as assembly items to improve assembly performance
Kathmann, Tom; Reh, Daniel; Arlinghaus, Julia C.
In: Advances in industrial and manufacturing engineering - [Amsterdam] : Elsevier ScienceDirect, Bd. 6 (2023), Artikel 100111, insges. 16 S.
Offering subscriptions of industrial goods - uncertain experiment or necessary step?
Burger, Markus; Krüger, Andreas; Burgmann, Nils; Arlinghaus, Julia C.
In: IRE transactions on engineering management / Institute of Radio Engineers - New York, NY : IEEE . - 2023, insges. 15 S. [Online first]
Scientific monograph
Wo geht das Fax hin? - Changemanagement und die digitale Transformation in der psychosozialen Beratung : eine zusammenfassende Studiendarstellung
Gaubiz, Eugenie; Ebert, Katharina; Förster, Marcel; Schlicht, Friedemann; Arlinghaus, Julia C.
In: Magdeburg: Universitätsbibliothek, 2023, 1 Online-Ressource (33 Seiten, 9,17 MB) [Förderkennzeichen BMBF 02L18A170-174; Verbundnummer: 01218914; Laufzeit: 01.06.2020-31.05.2023; Literaturverzeichnis: Seite 30; Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden]
2022
Book chapter
Managing supply chain disruption by collaborative resource sharing
Keßler, Melanie; Arlinghaus, Julia C.
In: Supply Network Dynamics and Control - Cham : Springer International Publishing . - 2022, S. 79-93
Maturity evaluation for workforce management - an integrated approach to assess digital maturity of workforce management systems
Häberer, Sebastian; Arlinghaus, Julia C.
In: Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future , 1st ed. 2022. - Cham : Springer International Publishing ; Borangiu, Theodor, S. 303-316 - (Studies in Computational Intelligence; volume 1034) [Workshop: 11th International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA 2021, 8-19 November 2021]
Management for digitalization and Industry 4.0
Arlinghaus, Julia C.; Antons, Oliver
In: Handbook Industry 4.0 , 1st ed. 2022. - Berlin, Heidelberg : Springer Berlin Heidelberg ; Frenz, Walter, S. 927-948
Machine learning and autonomous control - a synergy for manufacturing
Antons, Oliver; Arlinghaus, Julia C.
In: Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future , 1st ed. 2022. - Cham : Springer International Publishing ; Borangiu, Theodor, S. 417-428 - (Studies in Computational Intelligence; volume 1034) [Workshop: 11th International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA 2021, 8-19 November 2021]
Peer-reviewed journal article
Cognitive biases and the detection of production disruptions
Breiter, Stephan; Kessler, Melanie; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 107 (2022), S. 1397-1402 [Konferenz: 55th CIRP Conference on Manufacturing Systems 2022]
A manufacturing scheduling complexity framework and agent-based comparison of centralized and distributed control approaches
Antons, Oliver; Arlinghaus, Julia C.
In: IEEE journal of emerging and selected topics in industrial electronics - New York, NY : The Institute of Electrical and Electronics Engineers, Bd. 3 (2022), Heft 1, insges. 8 S.
Curse or blessing? - exploring risk factors of digital technologies in industrial operations
Keßler, Melanie; Arlinghaus, Julia C.; Rosca, Eugenia; Zimmermann, Manuel
In: International journal of production economics - Amsterdam [u.a.] : Elsevier Science, Bd. 243 (2022), Artikel 108323
Distributing decision-making authority in manufacturing - review and roadmap for the factory of the future
Antons, Oliver; Arlinghaus, Julia C.
In: International journal of production research - London [u.a.] : Taylor & Francis, Bd. 60 (2022), Heft 13, S. 4342-4360, insges. 19 S. [Online first]
Opportunities for synchronization in manufacturing as key performance indicator
Knapp, Florian; Antons, Oliver; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 107 (2022), S. 1467-1472 [Konferenz: 55th CIRP Conference on Manufacturing Systems 2022]
Understanding driving readiness - exploiting self-driving functions of autonomous vehicles to increase assembly performance
Kathmann, Tom; Reh, Daniel; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 107 (2022), S. 1017-1022 [Konferenz: 55th CIRP Conference on Manufacturing Systems 2022]
An industrial paradigm change - is subscribing the new buying?
Burger, Markus; Krüger, Andreas; Burgmann, Nils; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 107 (2022), S. 1023-1028 [Konferenz: 55th CIRP Conference on Manufacturing Systems 2022]
Data-driven and autonomous manufacturing control in cyber-physical production systems
Antons, Oliver; Arlinghaus, Julia C.
In: Computers in industry - Amsterdam [u.a.] : Elsevier Science, Bd. 141 (2022), Artikel 103711
A framework for human-centered production planning and control in smart manufacturing
Kessler, Melanie; Arlinghaus, Julia C.
In: Journal of manufacturing systems - Amsterdam [u.a.] : Elsevier Science, Bd. 65 (2022), S. 220-232
Sharing is caring? - von offener Software zu offener Hardware : Chancen und Herausforderungen durch Open-Source-Geschäftsmodelle
Arlinghaus, Julia C.; Behnert, Anna-Kristin; Kessler, Melanie
In: Industrie 4.0 Management - Berlin : GITO-Verl., Bd. 38 (2022), Heft 6, S. 24
On the development of a blockchain-implementable intermediation model for digital supply chains
Grassi, Andrea; Guizzi, Guido; Santillo, Liberatina C.; Vespoli, Silvestro; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 55 (2022), Heft 10, S. 946-951
Human-centricity in the design of production planning and control systems - a first approach towards Industry 5.0
Rannertshauser, Patrick; Kessler, Melanie; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 55 (2022), Heft 10, S. 2641-2646
Manual collection of data on disruptions - determinants to increase the intention to use
Breiter, Stephan; Gottwald, Jonas; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 55 (2022), Heft 10, S. 952-957
Applied machine learning for production planning and control - overview and potentials
Büttner, Konstantin; Antons, Oliver; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 55 (2022), Heft 10, S. 2629-2634
2021
Book chapter
The influence of cognitive biases in production logistics
Knapp, Florian; Kessler, Melanie; Arlinghaus, Julia C.
In: Dynamics in logistics - Cham, Switzerland : Springer ; Freitag, Michael . - 2021, S. 183-193
Learning distributed control for job shops - a comparative simulation study
Antons, Oliver; Arlinghaus, Julia C.
In: Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future , 1st ed. 2021. - Cham : Springer International Publishing ; Borangiu, Theodor, S. 193-202 [Workshop: 10th International Workshop on Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future, SOHOMA 2020, Paris, France, October 1-2, 2020]
Distorted risk management - how cognitive biases influence human decision-making
Arlinghaus, Julia C.; Kessler, Melanie
In: Hamburg : Funk ; Funk-Münchmeyer, Anja *1970-* . - 2021, S. 51-59
Smarter relationships? - the present and future scope of AI application in buyer-supplier Relationships
Nitsche, Anna-Maria; Burger, Markus; Arlinghaus, Julia C.; Schumann, Christian-Andreas; Franczyk, Bogdan
In: Computational Logistics , 1st ed. 2021. - Cham : Springer International Publishing ; Mes, Martijn, S. 237-251 - (Lecture notes in computer science; volume 13004) [Konferenz: 12th International Conference on Computational Logistics, ICCL 2021, Enschede, The Netherlands, September 27-29, 2021]
Digital supplier integration - transaction 4.0 in buyer-supplier relationships
Burger, Markus; Arlinghaus, Julia C.
In: Supply management research / Supply Management , 2021 - Wiesbaden : Springer Gabler, S. 211-232 [Literaturangaben]
Risk assessment and mitigation for Industry 4.0 - implementation of a digital risk quick check
Arlinghaus, Julia C.; Bendik, Falko
In: Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems , 1st ed. 2021. - Cham : Springer International Publishing ; Dolgui, Alexandre, S. 208-217 - ( IFIP advances in information and communication technology; volume 630) [Konferenz: International Conference on Advances in Production Management Systems, APMS 2021, Nantes, France, September 5-9, 2021]
Exploring interdependency effects of production orders as central impact factors of logistics performance in manufacturing systems
Vican, Victor; Arlinghaus, Julia C.
In: Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems , 1st ed. 2021. - Cham : Springer International Publishing ; Dolgui, Alexandre, S. 180-187 - ( IFIP advances in information and communication technology; volume 630) [Konferenz: International Conference on Advances in Production Management Systems, APMS 2021, Nantes, France, September 5-9, 2021]
The influence of cognitive biases in production planning and control - considering the human factor for the design of decision support systems
Arlinghaus, Julia C.; Zahner, Melanie
In: Human 4.0 - London : IntechOpen Limited . - 2021, insges. 12 S. [Chapter 5]
Peer-reviewed journal article
Decision support for frugal products and production systems based on Product-Process-Resource-Skill & Variability models
Fidan, Yazgül; Lüder, Arndt; Meixner, Kristof; Baumann, Laura; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 104 (2021), S. 1619-1625
Disruption data collection in low-volume, complex product assembly
Breiter, Stephan; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 54 (2021), Heft 1, S. 80-85
Algorithm-use in the field of lean management principles - state of the art and need for research
Baumann, Laura; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 54 (2021), Heft 1, S. 504-509
Assessing and mitigating the risk of digital manufacturing - development and implementation of a digital risk management method
Arlinghaus, Julia C.; Rosca, Eugenia
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 54 (2021), Heft 1, S. 337-342
Distributed control for Industry 4.0 - a comparative simulation study
Antons, Oliver; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 54 (2021), Heft 1, S. 516-521
Flexible workforce allocation as driver of economic and human-oriented shop floor organization
Häberer, Sebastian; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 104 (2021), S. 1680-1685
Aiming for Industry 4.0 maturity? - the risk of higher digitalization levels in buyer-supplier relationships
Burger, Markus; Kessler, Melanie; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 104 (2021), S. 1529-1534
Disruption attributes for low-volume, complex product assembly
Breiter, Stephan; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 104 (2021), S. 1710-1715
Propositions on the benefits of the organizational education perspective towards realizing Industry 4.0-promises
Keller, Alinde; Weber, Susanne M.; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 104 (2021), S. 1734-1740
Lernen von den Vorreitern? - Dimensionen von Subscription Business Models im industriellen Kontext
Burgmann, Nils; Burger, Markus; Krüger, Andreas; Arlinghaus, Julia C.
In: atp Magazin - Essen : Vulkan Verlag GmbH, Bd. 63 (2021), Heft 11-12, S. 92-100
Adaptive self-learning distributed and centralized control approaches for smart factories
Antons, Oliver; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 104 (2021), S. 1577-1582
Article in conference proceedings
Den Widerspruch zwischen Effizienz, Flexibilität und Nachhaltigkeit auflösen
Arlinghaus, Julia C.
In: KI und Nachhaltigkeit / Schulzki-Haddouti , Christiane , Stand: Juni 2021 - München : Lernende Systeme, Plattform für Künstliche Intelligenz ; Schulzki-Haddouti, Christiane, S. 151-161
Risikomanagement für die Smarte Fabrik - Potenziale der Digitalisierung erschließen - Risiken aktiv managen
Arlinghaus, Julia C.; Bendik, Falko; Fidan, Yazgül; Kessler, Melanie; Reinecke, Laura
In: Magdeburg: Otto-von-Guericke-Universität, Lehrstuhl für Produktionssysteme und -automatisierung, 2021, 1 Online-Ressource (circa 48 Seiten)
Scientific monograph
Resilienz - ein Fraunhofer-Konzept für die Anwendung
Hiermaier, Stefan; Hiller, Daniel; Edler, Jakob; Roth, Florian; Arlinghaus, Julia C.; Clausen, Uwe
In: Fraunhofer-Gesellschaft, 2021, 1 Online-Ressource
2020
Book chapter
Neue Technologien = neue Risiken? - wie Industrie 4.0 die Risikolandschaft in Produktion und Logistik verändert und wie Unternehmen ihr Risikomanagement daran anpassen müssen
Arlinghaus, Julia C.; Zimmermann, Manuel
In: Insurance & Innovation 2020 , 1. Auflage - Karlsruhe : VVW GmbH ; Eckstein, Andreas, S. 137-147
Management für Digitalisierung und Industrie 4.0
Arlinghaus, Julia C.; Antons, Oliver
In: Handbuch Industrie 4.0: Recht, Technik, Gesellschaft , 1st ed. 2020. - Berlin, Heidelberg : Springer Berlin Heidelberg ; Frenz, Walter, S. 1121-1145
Modelling autonomous production control - a guide to select the most suitable modelling approach
Antons, Oliver; Arlinghaus, Julia C.
In: Dynamics in Logistics , 1st ed. 2020. - Cham : Springer International Publishing ; Freitag, Michael, S. 245-253 - ( Advances in Intelligent Systems and Computing; volume 1026; 2nd International Conference on Human Systems Engineering and Design, IHSED2019, München, September 16-18, 2019)
The influence of cognitive biases on supply chain risk management in the context of digitalization projects
Arlinghaus, Julia C.; Zimmermann, Manuel; Zahner, Melanie
In: Dynamics in Logistics , 1st ed. 2020. - Cham : Springer International Publishing ; Freitag, Michael, S. 137-147 - ( Advances in Intelligent Systems and Computing; volume 1026; 2nd International Conference on Human Systems Engineering and Design, IHSED2019, München, September 16-18, 2019)
Autonomous production control methods - job shop simulations
Zhao, Ziqi; Antons, Oliver; Arlinghaus, Julia C.
In: Dynamics in Logistics , 1st ed. 2020. - Cham : Springer International Publishing ; Freitag, Michael, S. 227-235 - ( Advances in Intelligent Systems and Computing; volume 1026; 2nd International Conference on Human Systems Engineering and Design, IHSED2019, München, September 16-18, 2019)
Peer-reviewed journal article
Frugal processes - an empirical investigation into the operations of resource-constrained firms
Knizkov, Stephanie; Arlinghaus, Julia C.
In: IRE transactions on engineering management / Institute of Radio Engineers - New York, NY : IEEE . - 2020, insges. 18 S. [Online first]
Designing decision-making authorities for smart factories
Antons, Oliver; Arlinghaus, Julia C.
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 93 (2020), S. 316-322 [Part of special issue: 53rd CIRP Conference on Manufacturing Systems 2020]
Lean maintenance and repair implementation - a cross-case study of seven automotive service suppliers
Arlinghaus, Julia C.; Knizkov, Stephanie
In: Procedia CIRP / CIRP - The International Academy for Production Engineering - Amsterdam [u.a.] : Elsevier, Bd. 93 (2020), S. 955-964 [Part of special issue: 53rd CIRP Conference on Manufacturing Systems 2020]
Scientific monograph
Perspektiven regionaler Lieferketten und Nutzung neuer Wirtschaftspotenziale durch Produktions (Rück-)verlagerungen für Sachsen-Anhalt
Arlinghaus, Julia C.; Sondej, Franziska; Blobner, Christian
In: Magdeburg: Fraunhofer IFF, 2020, 1 Online-Ressource (55 Seiten)
2019
Book chapter
Understanding the influence of cognitive biases in production planning and control
Arlinghaus, Julia C.; Zahner, Melanie
In: Human Systems Engineering and Design II , 1st ed. 2020 - Cham : Springer ; Ahram, Tareq . - 2019, S. 280-285 - (Advances in Intelligent Systems and Computing; 1026) [Konferenz: 2nd International Conference on Human Systems Engineering and Design,IHSED2019, München, September 16-18, 2019]
Decision making in Industry 4.0 - a comparison of distributed control approaches
Antons, Oliver; Arlinghaus, Julia C.
In: Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future , 1st ed. 2020 - Cham : Springer ; Borangiu, Theodor . - 2019, S. 329-339 - (Studies in computational intelligence; 853) [Workshop: International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA 2019, València, 3-4 October 2019]
The influence of cognitive biases in production planning and control - considering the human factor for the design of decision support systems
Arlinghaus, Julia C.; Zahner, Melanie
In: Human 4.0 - IntechOpen . - 2019 [Online first]
An improved production planning approach under the consideration of production order interdependencies
Arlinghaus, Julia C.; Vican, Victor; Hütt, Marc-Thorsten
In: Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future , 1st ed. 2020 - Cham : Springer ; Borangiu, Theodor . - 2019, S. 232-243 - (Studies in computational intelligence; 853) [Workshop: International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA 2019, València, 3-4 October 2019]
Peer-reviewed journal article
Resource sharing as supply chain disruption risk management measure
Cockx, Ronald; Armbruster, Dieter; Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 52 (2019), Heft 13, S. 802-807 [Konferenz: 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019, Berlin, Germany, 28-30 August 2019]
Value chain integration of base of the pyramid consumers - an empirical study of drivers and performance outcomes
Rosca, Eugenia; Arlinghaus, Julia C.
In: International business review - Amsterdam [u.a.] : Elsevier, Bd. 28 (2019), Heft 1, S. 162-176
Inclusive operations at the base of the pyramid: sustainable value creation for mitigating social exclusion
Arlinghaus, Julia C.; Rosca, Eugenia
In: Logistics research - Berlin : Springer - Volume 12 (2019), issue 1, article 10
Is co-creation always sustainable? - empirical exploration of co-creation patterns, practices, and outcomes in bottom of the pyramid markets
Knizkov, Stephanie; Arlinghaus, Julia C.
In: Sustainability - Basel : MDPI - Volume 11 (2019), issue 21, article 6017, 22 Seiten
The design space of production planning and control for industry 4.0
Arlinghaus, Julia C.; Blunck, Henning
In: Computers in industry - Amsterdam [u.a.] : Elsevier Science, Bd. 105 (2019), S. 260-272
Supply chain inclusion in base of the pyramid markets - a cluster analysis and implications for global supply chains
Rosca, Eugenia; Möllering, Guido; Rijal, Arpan; Arlinghaus, Julia C.
In: International journal of physical distribution and logistics management - Bingley : Emerald, Bd. 49 (2019), Heft 5, S. 575-598
Evolution of global manufacturing networks and xKD supply chains - a cross case study of six global automotive manufacturers
Arlinghaus, Julia C.; Erfurth, Toni
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 52 (2019), Heft 13, S. 1349-1354 [Konferenz: 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019, Berlin, Germany, 28-30 August 2019]
Understanding the meaning of human perception and cognitive biases for production planning and control
Arlinghaus, Julia C.
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 52 (2019), Heft 13, S. 2201-2206 [Konferenz: 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019, Berlin, Germany, 28-30 August 2019]
Supply chain risks in times of Industry 4.0 - insights from German cases
Arlinghaus, Julia; Zimmermann, Manuel; Antons, Oliver; Rosca, Eugenia
In: IFAC-PapersOnLine / Internationale Förderung für Automatische Lenkung - Frankfurt : Elsevier, Bd. 52 (2019), Heft 13, S. 1755-1760 [Konferenz: 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019, Berlin, Germany, 28-30 August 2019]
Editor
2018
Peer-reviewed journal article
Does frugal innovation enable sustainable development? - a systematic literature review
Rosca, Eugenia; Reedy, Jack; Arlinghaus, Julia C.
In: The European journal of development research - [S.l.] : Palgrave Macmillan, Bd. 20 (2018), Heft 1, S. 136-157
Influencing factors of synchronization in manufacturing systems
Chankov, Stanislav; Hütt, Marc-Thorsten; Arlinghaus, Julia C.
In: International journal of production research - London [u.a.] : Taylor & Francis, Bd. 56 (2018), Heft 14, S. 4781-4801
Understanding synchronizability of manufacturing networks - a multi-method study on structural network properties
Chankov, Stanislav; Hütt, Marc-Thorsten; Arlinghaus, Julia C.
In: Journal of manufacturing systems - Amsterdam [u.a.] : Elsevier Science, Bd. 46 (2018), S. 127-136
Setting production capacities for production agents making selfish routing decisions
Blunck, H.; Armbruster, D.; Arlinghaus, Julia C.
In: International journal of computer integrated manufacturing - London [u.a.] : Taylor & Francis, Bd. 31 (2018), Heft 7, S. 664-674
The balance of autonomous and centralized control in scheduling problems
Blunck, Henning; Armbruster, Dieter; Arlinghaus, Julia C.; Hütt, Marc-Thorsten
In: Applied network science - [Cham] : Springer International Publishing - Volume 3 (2020), issue 1, article 16, 19 Seiten
Integration of global manufacturing networks and supply chains: a cross case comparison of six global automotive manufacturers
Erfurth, Toni; Arlinghaus, Julia C.
In: International journal of production research - London [u.a.] : Taylor & Francis, Bd. 56 (2018), Heft 22, S. 7008-7030
2017
Book chapter
Application potential of multidimensional scaling for the design of DSS in transport insurance
Vican, Victor; Blindu, Ciprian; Fofonov, Alexey; Ucinska, Marta; Arlinghaus, Julia C.; Linsen, Lars
In: Dynamics in Logistics - Cham : Springer ; Freitag, Michael . - 2017, S. 109-118 [Konferenz: 5th International Conference LDIC, 2016 Bremen, Germany]
Exploring the design space for myopia-avoiding distributed control systems using a classification model
Wang, Tianyi; Blunck, Henning; Arlinghaus, Julia C.
In: Service Orientation in Holonic and Multi-Agent Manufacturing - Cham : Springer ; Borangiu, Theodor . - 2017, S. 295-304 - ( Studies in Computational Intelligence; volume 694) [Workshop: International Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA 2016]
Peer-reviewed journal article
Business models for sustainable innovation - an empirical analysis of frugal products and services
Rosca, Eugenia; Arnold, Marlen; Arlinghaus, Julia C.
In: Journal of cleaner production - Amsterdam [u.a.] : Elsevier Science - Volume 162 (2017), Supplement, Seite S133-S145
Sustainable supply chain models for base of the pyramid
Arlinghaus, Julia C.; Rosca, Eugenia; Pivovarova, Darima
In: Journal of cleaner production - Amsterdam [u.a.] : Elsevier Science - Volume 162 (2017), Supplement, Seite S107-S120
An analytical approach to improving due-date and lead-time dynamics in production systems
Duffie, N.; Arlinghaus, Julia C.; Knollmann, M.
In: Journal of manufacturing systems - Amsterdam [u.a.] : Elsevier Science, Bd. 45 (2017), S. 273-285
2016
Peer-reviewed journal article
The elementary flux modes of a manufacturing system: a novel approach to explore the relationship of network structure and function
Meyer, Mirja; Hütt, Marc-Thorsten; Arlinghaus, Julia C.
In: International journal of production research - London [u.a.] : Taylor & Francis, Bd. 54 (2016), Heft 14, S. 4145-4160
Synchronization emergence and its effect on performance in queueing systems
Schipper, Manuel A.; Chankov, Stanislav M.; Arlinghaus, Julia C.
In: Procedia CIRP - Amsterdam [u.a.] : Elsevier, Bd. 52 (2016), S. 90-95
What is really on-time? - a comparison of due date performance indicators in production
Schäfer, Ricarda; Chankov, Stanislav; Arlinghaus, Julia C.
In: Procedia CIRP - Amsterdam [u.a.] : Elsevier, Bd. 52 (2016), S. 124-129
Lead time instability and its mitigation in production work systems
Duffie, Neil; Arlinghaus, Julia C.; Windt, Katja; Knollmann, Mathias
In: CIRP annals, manufacturing technology - Paris : CIRP, Bd. 65 (2016), Heft 1, S. 437-440
Long-term capacity planning in die manufacturing using the estimated product cost - an exploratory research
Apostu, Marius-Vasile; Arlinghaus, Julia C.
In: Procedia CIRP - Amsterdam [u.a.] : Elsevier, Bd. 41 (2016), S. 39-44
Simultaneous workload allocation and capacity dimensioning for distributed production control
Blunck, Henning; Armbruster, Dieter; Arlinghaus, Julia C.
In: Procedia CIRP - Amsterdam [u.a.] : Elsevier, Bd. 41 (2016), S. 460-465
Exploring impact factors of shippers risk prevention activities - a European survey in transportation
Arlinghaus, Julia C.; Skorna, Alexander C. H.
In: Transportation research / E - Oxford : Pergamon, Elsevier Science, Bd. 90 (2016), S. 206-223
The human factor in production planning and control - considering human needs in computer aided decision-support systems
Arlinghaus, Julia C.; Knollman, Mathias
In: International journal of manufacturing technology and management - Genéva : Inderscience Enterprises, Bd. 30 (2016), Heft 5, S. 346
The lead time syndrome of manufacturing control - comparison of two independent research approaches
Arlinghaus, Julia C.; Knollmann, Mathias
In: Procedia CIRP - Amsterdam [u.a.] : Elsevier, Bd. 41 (2016), S. 81-86
Synchronization in manufacturing systems - quantification and relation to logistics performance
Chankov, Stanislav; Hütt, Marc-Thorsten; Arlinghaus, Julia C.
In: International journal of production research - London [u.a.] : Taylor & Francis, Bd. 54 (2016), Heft 20, S. 6033-6051
2015
Book chapter
Sustainable technology transfer for poverty alleviation - a unified framework for challenges and transdisciplinary solution approaches
Arlinghaus, Julia C.; Rosca, E.; Hoffmann, T.
In: Sustainable Development and Planning VII / Özçevik , Ö - Ashurst : WIT Press ; Özçevik, Ö . - 2015, S. 823-834
Current projects
Gamelab Saxony-Anhalt - Research and development platform for applied immersive games
Duration: 01.01.2024 bis 31.12.2027
Companies in Saxony-Anhalt are facing major challenges. Innovations help to overcome these challenges by offering creative solutions and enabling new perspectives and more efficient approaches. Applied immersive games - to be understood as a human-centered and sustainable innovation method - are attractive for Generation Z (talent acquisition), can be used as a tool for lifelong learning (Industry 5.0) of all employees, a central basis for securing implicit experience knowledge (shortage of skilled workers), indispensable in the context of future-oriented training as well as for qualifications and further training participation (training purposes) and an ideal instrument for raising awareness of cutting-edge technologies in the context of digital learning systems.
Project objective
The aim is to establish a research and development platform for applied immersive games which, through the synergy of science and business, enables companies in the country to address the challenges of the working world by means of human-centered innovations and to develop solutions. The project is pursuing research into an (integrative) modular principle.
The Gamelab Saxony-Anhalt project is funded by the European Regional Development Fund (ERDF) for the project period from 2024 to 2027.
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OpenDANS - Open Data for Sustainable and Scalable Production Research
Duration: 01.01.2024 bis 31.12.2027
Artificial intelligence (AI) methods are increasingly becoming a critical competitive factor for companies and science in Saxony-Anhalt. Universities and research institutions are providing impetus for the development of new planning, control and optimization methods and AI applications. Production and logistics companies use these methods to continuously increase efficiency, flexibility and sustainability. The OpenDANS project aims to synergistically network both players. The aim of the project is to create an open source database for real data and AI applications that companies and researchers can access free of charge. Researchers will have access to real data sets, which will significantly increase research results, particularly in terms of application proximity. Companies gain direct access to methods and analysis approaches.
Following the example of biology and medical research, such as the establishment of the Human Genome Project as an open database, OpenDANS also aims to unleash disruptive potential for production and logistics research. The resulting database will become the basis for scientists worldwide and allow them to build on each other's results. The open exchange of standardized real data sets creates synergy, improves the applicability and scalability of research results in the field of AI and digital twins. This brings considerable benefits for scientists, for Saxony-Anhalt as a science location and for the efficiency and sustainability of local companies.
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SmartRegion Saxony-Anhalt
Duration: 01.01.2024 bis 31.12.2027
The adoption of new technologies, the integration of existing ecological and technical systems, and the interconnection of various economic sectors that shape regional residents' lives are now essential aspects of daily life in the 21st century. Historically, key sectors such as energy, water, transportation, and housing were treated separately and independently, each with its own set of criteria.
There is now a need to explore innovative models that can unify the current energy landscape, agricultural state, and transportation infrastructure with sustainable and healthy living standards for residents. This holistic approach encompasses water usage and waste management, aiming to bring these elements together in a cohesive model.
The project seeks to create models and tools for integrative planning and cross-sector operations in Saxony-Anhalt. It will focus on interconnecting the fields of energy, water and wastewater, housing and living, and mobility and transportation.
Research will be conducted in partnership with experts in energy (Prof. Dr.-Ing. Przemyslaw Komarnicki, Magdeburg University of Applied Sciences), housing and living (Prof. Dr. rer. nat. Olaf Ueberschär, Magdeburg University of Applied Sciences), water, drinking water, and wastewater (Prof. Dr.-Ing. Bernd Ettmer and Prof. Dr.-Ing. habil. Jürgen Wiese, Magdeburg University of Applied Sciences), as well as mobility and transportation (Prof. Dr. oec. Julia Arlinghaus, Otto von Guericke University Magdeburg). The overarching goal is to develop a sustainable and future-ready Saxony-Anhalt.
Quick Check Sustainability Risks
Duration: 01.10.2022 bis 30.09.2025
The aim of this research project is to develop an online-based toolkit for the initial assessment of sustainability and ESG risks. Building on and complementing the two quick check tools Supply Chain Quick Check and Digital Quick Check, the findings will be transferred into a new, web-based tool that offers industrial companies a free and low-cost basis for the initial assessment of reputational and sustainability risks and possible countermeasures.
Cooperation: Funk Foundation
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Completed projects
The Implementation of Industry 4.0 in buyer-supplier relationships
Duration: 01.01.2021 bis 31.12.2024
The research topic examines how the introduction of Industry 4.0 at the supplier-customer interface affects in particular the cooperation between companies, business models and the underlying risks. The focus is on a consideration of different levels of digital maturity of suppliers and customers. Through his work on an E2E resilience approach in the context of a digital twin of the Siemens supply chain, he incorporates findings from practical risk management into his research.
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Disruption Data Management in Low-volume Assembly Systems
Duration: 01.01.2021 bis 31.12.2024
In the final assembly of complex small series products, the corresponding assemblies, modules and individual parts are produced with a high level of manual effort and a low level of automation. Within this value creation process, disruptions occur for various reasons such as missing parts, missing employees, machine malfunctions and quality problems. These have a negative impact on key performance indicators such as costs and delivery. The research focuses on the human factors involved in the detection and recording of faults as employees interact with the assembly system. The aim is to develop a procedure that efficiently records fault data manually and based on fault events at an appropriate level of detail and explains deviations between planned and target throughput times with a high degree of reliability. The information generated in this way serves as a starting point for improving the value creation process.
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Exploiting self-driving functions of autonomous vehicles to increase assembly performance
Duration: 01.01.2021 bis 31.12.2024
The automotive industry is facing the transition to autonomous vehicles. At the same time, assembly systems are confronted with high flexibility requirements. The project deals with the development of potentials resulting from the use of the technological basis, such as sensor technology and image recognition, of autonomous vehicles as assembly objects and aims to use the self-driving function already in assembly systems in order to reduce the required conveyor technology. The work focuses on the definition of minimum requirements for the autonomous vehicle in the assembly environment, the necessary reorganization of the assembly sequence in order to make the function usable as early as possible, and the use of more flexible assembly structures from the time the vehicle is ready to drive in assembly.
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Excellence Cluster Initiative "Cognitive Vitality" - Subproject Workshops - Recovery Promotion
Duration: 01.12.2022 bis 31.12.2024
Within the Cluster of Excellence Initiative: Cognitive Vitality, the Chair of PSA, in collaboration with the Neuropsychology research group at OVGU and the Digital Assistance Systems working group at the Fraunhofer Institute IFF, is implementing a project in the "Regeneration Support" workshop. The aim is to establish a new measurement method for the objective assessment of cognitive fatigue, on the basis of which, among other things, the potential of cognitive assistance systems can be evaluated. In an initial laboratory study, correlations with the occurrence of increased cognitive strain are currently being determined on the basis of electroencephalography (EEG) and respiratory gas testing. The transferability of the results to the real industrial environment is to be investigated in follow-up studies.
The Cluster of Excellence Initiative: Cognitive Vitality strives to overcome the traditional boundaries between different scientific fields in an integrative approach. We want to understand which neuronal, somatic and social factors determine cognitive vitality and strive for a paradigmatic and transferable innovation ranging from basic research to prevention and intervention. In doing so, we build on Magdeburg's history in neural circuit research.
Overall project management. Prof. Dr. Emrah Düzel
You can find more information about the project here: https://cognitive-vitality.de/
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Productive Teaming research initiative - sub-project "Improved collaboration between man and machine in the production process"
Duration: 01.01.2023 bis 31.12.2024
In the face of rapid technological advances, the forward-looking vision of the Productive Teaming research initiative is to take human-machine collaboration to a new level. The aim is to enable a new generation of dynamic human-machine teams in production systems that can master more complex and adaptive challenges than current cyber-physical systems or human teams.
Instead of conventional production automation, which relies heavily on fixed, predefined processes, teaming production systems should focus on maintaining the flexibility and adaptability of production processes. To this end, the innate human ability to react and adapt agilely to disruptions, such as errors from previous process steps or required input quantities for semi-finished products, should also be realized at machine level. Instead of aiming for maximum automation and the associated need to standardize production processes, the "Productive Teaming" research initiative aims to enable maximum flexibility and dynamization of production, both in terms of the individual production steps and the design of the finished product (batch size 1). This paradigm shift promotes the emergence of adaptive manufacturing processes, the improvement of working conditions, greater sustainability and greater product individualization, which takes into account the challenges of Industry 5.0.
To realize these goals, intelligent systems should be improved to i) draw conclusions on a cognitive level, ii) coordinate interdependent actions for seamless, goal-oriented and coherent teamwork, iii) design joint action plans and iv) create trust and acceptance through transparency in decision-making. The resulting new level of human-machine symbiosis leads to more flexibility in the production landscape, less material and energy consumption and a general reduction in cognitive and physical stress for human employees.
b]"Productive Teaming" is a joint research initiative of Chemnitz University of Technology, Ilmenau University of Technology and OVGU Magdeburg. The three universities complement each other perfectly in the network, which is dedicated in particular to human-technology interaction and will also expand into other research areas in the future. Each of the three universities contributes its own special expertise - Chemnitz University of Technology in the field of "Human-Machine Interaction and Cognitive Systems", Ilmenau University of Technology in the field of "Intelligent Sensors and Complex Systems" and OVGU Magdeburg in the research field of "Artificial Intelligence and Digital Engineering".
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Machine learning in production planning and control
Duration: 01.01.2021 bis 31.12.2024
Production planning and control has to cope with increased complexity, uncertainty and dynamic, which makes it more difficult for companies to achieve their production logistical targets. At the same time, the increasing use of cyber-physical systems has led to a significant larger amount of information available in near real time, that can be used for planning and control tasks. However, conventional methods of production planning and control have difficulties processing this enlarged amount of information and filtering aspects that are relevant for decision-making. Therefore, the aim of this project is to research the extent to which production planning and control can be improved by machine learning methods and which barriers currently impede its implementation.
Human-centricity in the design of production planning and control systems
Duration: 01.01.2021 bis 31.12.2024
In the areas of production planning and control (PPC), the production planner is confronted with uncertainties and high complexity, and therefore decision support systems are used to support them. In the context of Industry 4.0 these technical solutions focus primarily on the use of machines and less on people, which means that the human perspective in the form of needs and cognitive biases is often neglected. This problem is to be solved by the human-centred approach of Industry 5.0 in PPC by this project. Existing PPC systems and their development models of decision support systems in PPC will be analyzed, questioned and further developed by the human-centred approach under consideration of cognitive biases.
Frugal Production and Supply Chain Design
Duration: 01.01.2021 bis 31.12.2024
In recent years, various crises have highlighted the fragility of global supply chains. In particular, climate change and rising energy prices are drawing attention to the enormous waste of resources caused by the linear economic model. The circular economy is seen as a promising alternative to tackle these challenges. For a systematic transformation, companies need to review and redesign their business models, product lifecycles and fundamental assumptions. Cross-industry collaboration in networks is becoming increasingly important in order to develop, reuse and recycle products to close the material loop.
In our research on open source as an enabler for the circular economy, we systematically analyze the necessary changes in companies' product development, manufacturing and distribution processes to ensure a sustainable shift towards a circular economy. Our aim is to formulate clear principles and specific methods for using open concepts as catalysts for the circular economy. These can be used by a wide range of companies to foster innovation, increase competitiveness, improve resource efficiency and facilitate and accelerate the transition to a circular economy.
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Supply Chain Quick Check and Digital Quick Check
Duration: 01.01.2021 bis 31.12.2024
Ten years after the introduction of the term Industry 4.0, it is clear that much of the potential has not yet been realized. This is because risks associated with Industry 4.0 projects are often not managed systematically. Based on the online tools "Quick Check - The Supply Chain Analysis Tool" and "Digital Quick Check" developed in cooperation with the Funk Foundation, companies have tools at their disposal to check their own supply chain and digitalization projects for risks of various kinds in a low-cost and intuitively understandable way. As part of this project, functional enhancements are being designed and implemented for both tools.
Supply Chain Quick Check: https://supplychain.risk-quickcheck.de/de/
Digital Quick Check: https://risk-quickcheck.de
Funding body: Funk Foundation
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Investigation of the application potential of inertial sensor-based motion capture systems for ergonomics evaluation
Duration: 01.06.2022 bis 31.12.2024
Modern motion capture systems offer great advantages in the ergonomic evaluation of existing workstations, for example in terms of objectivity and time savings. To date, optical motion capture systems in particular have been used for this purpose, which are characterized by high accuracy, but also require a great deal of set-up effort. Inertial sensor-based systems offer more potential for flexible use, but are rarely used for this purpose as they are considered less reliable, particularly due to the so-called "drift". In view of the technological progress in sensor technology in combination with ever finer sensor fusion algorithms, it will first be examined whether the data collected is actually not sufficiently accurate for ergonomics assessment or which factors have a negative influence on the measurement result. This will then be used to determine the conditions under which the use of such a system is recommended.
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Potentials for the performance of production systems by taking employee preferences into account in personnel resource planning
Duration: 01.01.2021 bis 30.09.2024
A shortage of skilled workers, an increase in sick days due to mental illness, the demands of "Generation Y" (and "Generation Z"), employer attractiveness as a key competitive factor, globalization, decentralization and digitalization - the list of trends, currents and other influencing factors that are constantly increasing the requirements for modern, economical and humane working time and work organization is long. A major problem for increasing employer attractiveness is fully continuous shift work, to which there are currently hardly any alternatives in the production industry. Shift work enjoys an extremely poor reputation among the employees concerned and their families, but also among potential applicants. This doctoral project is therefore investigating the effects of taking employee preferences into account when designing working hours and work organization on the performance of production systems.
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Cluster of Excellence Initiative SmartProSys: Intelligent Process Systems for Sustainable Chemical Production" Subcluster / Subproject: Dynamic Closed Loop Management for Sustainable Chemicals
Duration: 01.09.2022 bis 30.06.2024
The Magdeburg research initiative SmartProSys (Smart Process Systems Engineering) investigates methods and approaches for the sustainable transformation of chemical, mechanical and biotechnological production processes towards a sustainable circular economy for a sustainable society. Scientists from the fields of logistics, mathematics, sociology, political science and psychology are involved in SmartProSys and are looking at the possibilities for this transformation in the clusters "Systems Engineering and Computational Methods", "Supply Chain and Sustainability Management" and "Societal Support and Individual Appropriation".
Sub-project: Dynamic Closed Loop Management for Sustainable Chemicals
The Chair of Production Systems and Automation is involved in the "Supply Chain and Sustainability Management" cluster and leads the sub-project "Dynamic Closed Loop Management for Sustainable Chemicals". A sustainable circular economy in the chemical industry poses new logistical challenges: Transport emissions, procurement from sources of varying quality and sustainability in a time-critical multidimensional optimization. The sub-project aims to create suitable models and simulations to support the overarching goal of a sustainable transformation of the circular economy in chemical production.
The research network pursues the goal of excellence as defined by the Excellence Initiative of the German federal and state governments.
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Frugal supply chain design and innovation
Duration: 01.01.2021 bis 30.11.2023
The research topic deals with different supply chain concepts and innovation approaches that companies can apply to successfully target the emerging middle class and low-income groups in developing countries. It provides practical guidance for companies on the following questions: How can companies develop frugal innovation capabilities, e.g. the development of highly affordable products? How can companies include people living in poverty in their supply chains in a socially responsible way? How can companies integrate new technologies into their supply chains, e.g. drone deliveries that can reach potential customers even in the most rural areas?
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Synchronization emergence in manufacturing systems and its effect on logistic performance
Duration: 01.03.2021 bis 31.08.2023
While synchronization phenomena, such as the rhythmic flashing of fireflies, the swaying of a stadium with soccer fans jumping to the beat and the synchronized clapping of theater guests, have been extensively studied in the natural sciences, the understanding of synchronization in production systems is incomplete. Initial analyses of empirical data from logistics and production systems show that higher synchronization is associated with poorer logistics performance. The DFG-funded research project aims to investigate the relevant triggers, influencing factors and cause-effect relationships.
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Cognitive biases in operations and supply chain management
Duration: 01.01.2021 bis 30.06.2023
Human decision-making processes are not rational. Rather, so-called cognitive biases influence our decision-making results with significant effects on various areas such as logistics performance, supply chain risk management, etc. Particularly in times of digitalization, the question therefore arises as to who is the better decision-maker, man or machine, and we need to create digital support systems to provide people with the best possible support in their decision-making.
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Technical and organizational work design in psychosocial counselling (TOAB)
Duration: 01.06.2020 bis 31.05.2023
By selecting and using suitable technologies, new types of work processes with digital services are created in the course of the project's work steps. The implementation of digital technologies helps to optimize the mental stress of the advisors as well as to improve the quality and efficiency of the advisory processes. In order to make the research and establishment of digitally supported, collaborative work processes sustainable and application-oriented, a participatory approach is sought. When selecting suitable technologies, additional concepts are to be developed that enable the provision of the technologies as a digital service, possibly in the form of a platform, in order to be able to exploit corresponding network effects (efficiency, scaling, data analysis, etc.) in further utilization.
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Technical and organizational work design in psychosocial counselling (TOAB)
Duration: 01.06.2020 bis 31.05.2023
From 06/22 the project management was handed over to Prof. Dr. oec. Julia Arlinghaus.
Here you will find details on the project Technical and organizational work design in psychosocial counselling (TOAB):
https://forschung-sachsen-anhalt.de/project/technische-organisatorische-arbeitsgestaltung-24553
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Technical and organizational work design in psychosocial counselling (TOAB)
Duration: 01.06.2020 bis 31.05.2023
The aim of the project is to develop digitally supported, collaborative work processes that support the work of interorganizational multi-professional teams from various psychosocial counselling facilities through accompanying occupational science research, IT support and the involvement of three practice partners.
By selecting and using suitable technologies, new types of work processes with digital services are created in the course of the project's work steps. The implementation of digital technologies helps to optimize the mental stress of the advisors as well as to improve the quality and efficiency of the advisory processes. In order to make the research and establishment of digitally supported, collaborative work processes sustainable and application-oriented, a participatory approach is sought. When selecting suitable technologies, additional concepts are to be developed that enable the technologies to be provided as a digital service, possibly in the form of a platform, in order to be able to exploit corresponding network effects (efficiency, scaling, data analysis, etc.) in further utilization.
Funding: BMBF and ESF Federal Government (EU) www.esf.de
Dr. Sonja Schmicker led the project until 05/22.
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Digital Quick Check
Duration: 01.01.2021 bis 31.12.2022
Ten years after the introduction of the term Industry 4.0, it is clear that much of the potential has not yet been realized. This is because risks associated with Industry 4.0 projects are often not managed systematically. The aim of the Digital Quick Check research project is to identify and structure the most relevant Industry 4.0 technologies in production and logistics. In addition, clusters of Industry 4.0 technologies that are frequently used together are identified and their associated risks and potential mitigation strategies are compared. The findings of the project were made available in the form of the Digital Quick Check for companies from industry, trade and logistics services. The findings were also prepared for other target groups.
Digital Quick Check: https://risk-quickcheck.de/
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Human factor in production, logistics and SCM - need for the transition from Industry 4.0 to 5.0
Duration: 01.01.2021 bis 31.12.2022
Despite the increasing automation in the production and logistics environment in the course of digitalization, people remain a key resource. The European Commission has therefore presented a concept for the further development of the Industry 4.0 vision towards Industry 5.0 in 2021, which focuses on people with the aim of creating a resilient, more sustainable and human-centered industry. As part of the research, design approaches for production, logistics and supply chain management are to be given as to how the human factor can be taken into account and what role human decision-making plays in this.
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Hybrid Control Architectures for Production Planning and Control
Duration: 01.01.2021 bis 31.12.2022
Traditional production planning and control starts with the collection of all available and relevant information, followed by its centralized evaluation, from which one global plan is derived. This method has established itself due to its excellent solution quality, however, it is plagued by its considerable and badly scaling computation requirements. Due to increasing
digilization of production systems, new and distributed control approaches became possible, in which products and machines can act autonomously and control production locally. This method is very robust and fast, but delivers initially only locally good decisions. In order to combine these decisions reliably to a global plan, the right distribution of decision making authority is essential. In this project, we study these distributions to achieve reliable, robust and fast production control approaches.
Hybrid Intelligence
Duration: 01.01.2021 bis 31.12.2022
Collaborative cooperation between humans and machines allows the strengths of human and artificial intelligence to be combined. By linking the research areas of psychology and operations management, the aim is to provide design approaches for the development of artificial intelligence, taking into account human needs in the production environment.
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Overcoming dynamic effects in production planning and control - cause-and-effect
Duration: 01.01.2021 bis 31.12.2022
First described by Mathel and Plossl in 1977, the lead time syndrome of planning management and control is still not fully understood today. The phenomenon arises in order-driven production systems in which poor system performance leads to frequent adjustments of the target times, which in turn worsen the system performance in the short term and thus trigger an adjustment of the target times. The research group has already investigated the influence of cognitive biases on this phenomenon in the past and found a strong correlation. Nevertheless, it is reasonable to assume that the network design of the production system also has an influence on the occurrence and manifestation of this phenomenon. The aim of this project is to investigate this in order to develop efficient avoidance or attenuation strategies for the lead time syndrome.
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Control concepts for production plants
Duration: 01.01.2021 bis 31.12.2022
The research topic focuses on control concepts for production plants. A fundamental aspect of this is research into the contrasts, potentials and possible applications for centralized control concepts on the one hand and distributed and autonomous control concepts on the other. The basis for the realization of these control concepts lies in the capabilities of so-called cyber-physical systems, i.e. production machines that have inherent data collection, data processing and communication capabilities. To research these concepts, Mr. Antons has created a simulation framework that maps all machines, products and other actors in a production network as agents and thus enables the emulation and evaluation of control concepts.
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Subscription-based business models - subscription instead of buying as a new strategic option for industrial practice
Duration: 01.01.2021 bis 31.12.2022
While subscription models have become established for multimedia streaming services (e.g., Netflix, Spotify), Industry 4.0 sets out the conditions which are necessary for bringing these models to the industrial sector. Frontrunners offer subscriptions e.g., for printing machine or aircraft turbines. Thus, firms are increasingly faced to evaluate the offering or procurement of industrial products within a subscription model. This project examines challenges and success factors of subscription models both, from a vendor`s and a buyer`s perspective. We put special emphasis on the complex ecosystem of digital, financial and insurance service providers that arises within the context of subscriptions.
ego.-INKUBATOR - Industrial science laboratory for the promotion of start-ups in the field of "Innovative Working World 4.0" (AWI-Lab II)
Duration: 01.11.2019 bis 31.10.2022
From 06/22 the project management was handed over to Prof. Dr. oec. Julia Arlinghaus.
Here you can find details about the project ego.-INKUBATOR - Laboratory for the promotion of start-ups in the "innovative working world 4.0 (AWI-Lab II):
https://forschung-sachsen-anhalt.de/project/ego-inkubator-arbeitswissenschaftliches-23260
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ego.-INKUBATOR - Ergonomics laboratory for the promotion of start-ups in the field of "Innovative Working World 4.0" (AWI-Lab II)
Duration: 01.11.2019 bis 31.10.2022
Advancing digitalization is changing current work processes in all areas of work. At the Chair of Ergonomics and Work Design at Otto von Guericke University Magdeburg, the human-digital laboratory of the world of work 4.0 is in operation and is being continuously expanded. The aim is to empower people as drivers of positive change in this development. The lab supports the creation of a start-up-oriented, occupational science infrastructure for the comprehensive development and testing of product, process and service innovations in the field of Working World 4.0, focusing in particular on the two lead markets identified by the state government of Saxony-Anhalt: "Energy, mechanical and plant engineering, resource efficiency" and "Health and medicine" (focus on the care of elderly and sick people). An assembly scenario 4.0, a care scenario 4.0 and a teamwork scenario 4.0 are available in the AWI Lab for this purpose.
Dr. Sonja Schmicker led the project until 05/22.
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Risk management 4.0
Duration: 01.05.2021 bis 31.12.2021
The aim of the proposed research project is to prepare the findings obtained as part of the "Digital Quick Check" research project in the form of a study. The study can serve as the basis and central medium for promoting the Digital Quick Check as a free online tool. In order to prepare the results for the diverse readership from industry, retail, logistics services, science, technology providers, the insurance industry and the interested public in an excellent way, the findings will also be underlined by interviews and case studies, the Industry 4.0 technologies will be illustrated with images and the statistical results will be visualized.
Project homepage:
https://www.psa.ovgu.de/Forschung/Studie+risk+management+for+the+smart+factory.html
Funding body: Funk Foundation
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