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Julia C. Arlinghaus received the Diploma degree in engineering management from the University of Bremen, Bremen, Germany, in 2007, and the Doctorate degree in business innovation focused on supply chain design, management and performance from the University of St. Gallen, St. Gallen, Switzerland, in 2011.
She is currently the Director of the Fraunhofer Institute for Factory Operation and Automation (IFF), Magdeburg, Germany. She was an Operational Excellence and Lean Management Consultant with Porsche until being appointed as an Associate Professor of Network Optimization in Production and Logistics with Jacobs University Bremen, Bremen, Germany, in 2013, and then a Professor of the Management of Industry 4.0 with the Rheinisch-Westflische Technische Hochschule Aachen, Aachen, Germany, in 2017. Together with her team, she researches in and provides businesses consulting services related to risk-optimized supply chain design, production planning and control system implementation, digitalized and efficient manufacturing operations, and frugal innovation and its implications for the design and management of manufacturing and logistics operations in developing countries.
Dr. Arlinghaus was the recipient of the DAAD Fellowship to attend the University of Tokyo. She holds the Chair of Production Systems and Automation with the Department of Mechanical Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany.
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论文共 65 篇作者统计合作学者相似作者
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Procedia Computer Science (2024): 2498-2507
Procedia Computer Science (2024): 1367-1376
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNALno. 2 (2024): 297-314
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCHno. 1-2 (2024): 204-222
Procedia Computer Science (2024): 436-445
Schwerpunkt Business Model Innovation Digitale Plattformen und Ökosysteme im B2B-Bereichpp.183-208, (2024)
IFAC PAPERSONLINEno. 2 (2023): 10327-10332
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENTno. 99 (2023): 1-15
2023 IEEE CONFERENCE ON ARTIFICIAL INTELLIGENCE, CAIpp.222-223, (2023)
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PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANIONpp.355-358, (2023)
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