Produktbild: Steel 4.0
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Steel 4.0 Digitalization in Steel Industry

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.07.2025

Herausgeber

Yilmaz Uygun + weitere

Verlag

Springer

Seitenzahl

187

Maße (L/B/H)

23,5/15,5/1,1 cm

Gewicht

342 g

Sprache

Englisch

ISBN

978-3-031-57470-2

Beschreibung

Portrait

Professor Dr. Dr.-Ing. Yilmaz Uygun studied Industrial Engineering at the FH Südwestfalen University of Applied Sciences and Logistics Engineering at the University of Duisburg-Essen. He earned a doctoral degree in engineering from TU Dortmund University/Fraunhofer IML and another one in logistics from the University of Duisburg-Essen. Afterward, he moved to the United States and joined the Industrial Performance Center of the Massachusetts Institute of Technology (MIT) to work as postdoctoral researcher. In 2016, he was appointed as a professor of Logistics Engineering, Technologies and Processes at Jacobs University Bremen (now Constructor University Bremen). Simultaneously, he is still a research affiliate at MIT. Throughout his career, he was involved in many basic and applied digitalization projects. Among his research interests is the development of novel approaches for production and logistics-related issues, such as inventory management, requirements management and scheduling.

Dr. Atilla Özgür earned his bachelor's degree in Electrical Engineering from Middle East Technical University (Ankara, Turkey) in 2003. After graduation, he worked as a professional software developer while continuing his academic studies. He earned his master's degree in Computer Engineering from Atılım University (Ankara, Turkey) in 2007 and his Ph.D. degree in Electrical Engineering from Başkent University (Ankara, Turkey) in 2017. His Ph.D. thesis was about applying machine learning and optimization methods to intrusion detection domain. In 2018, he joined Jacobs University Bremen (now Constructor University Bremen) as a postdoctoral researcher in a digitalization project in steel industry. For several years now, he is been applying his knowledge on machine learning, optimization and network analysis methods to steel production.

Professor Dr. Marc-Thorsten Hütt studied physics in Göttingen and Paris and received his Ph.D. in Göttingen in 1997. Following longer research stays in Novosibirsk, Paris, Warsaw and Darmstadt, he became an assistant professor of Theoretical Biology and Bioinformatics in 2001 at Darmstadt University of Technology. In 2006, he moved to Jacobs University (now Constructor University) in Bremen, accepting a Professorship in Computational Systems Biology. From 2000 to 2005, he was a member of "Die Junge Akademie," an institution founded by Berlin-Brandenburgische Akademie der Wissenschaften and Deutsche Akademie der Naturforscher Leopoldina. Since 2019, he is a member of the European Academy of Sciences and Arts. Among his research interests is the development of mathematical tools for analyzing spatiotemporal pattern formation and the relationship between topology and dynamics in complex networks. 

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.07.2025

Herausgeber

Verlag

Springer

Seitenzahl

187

Maße (L/B/H)

23,5/15,5/1,1 cm

Gewicht

342 g

Sprache

Englisch

ISBN

978-3-031-57470-2

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Steel 4.0
  • Introduction.- Planning and Scheduling of Electric Arc Furnace based Steelmaking.- Systematic review of steel surface defect detection methods on the open access datasets of Severstal and the Northeastern University (NEU).- Decision Support Systems for Steel Production Planning – State of the Art and Open Questions.- Volatility and Synchronization in Steel Manufacturing – A Simulation Study of a Modern Steel Mill.- A Comparison of Crossover Operators in Genetic Algorithms for Steel Domain.- Comparative Study of Two Genetic Algorithms for Steel Production Planning under Different Order Backlog Circumstances.- Effect of PolyLoss function on Steel defect detection.- Novel genetic algorithm for simultaneous scheduling of two distinct steel production lines.