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Steel 4.0digitalization in steel industry /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Steel 4.0edited by Yilmaz Uygun, Atilla Özgür, Marc-Thorsten Hütt.
Reminder of title:	digitalization in steel industry /
other author:	Özgür, Atilla.
Published:	Cham :Springer International Publishing :2024.
Description:	viii, 187 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Steel industry and tradeTechnological innovations.
Online resource:	https://doi.org/10.1007/978-3-031-57468-9
ISBN:	9783031574689$q(electronic bk.)

Steel 4.0digitalization in steel industry /
Steel 4.0digitalization in steel industry /[electronic resource] :edited by Yilmaz Uygun, Atilla Özgür, Marc-Thorsten Hütt. - Cham :Springer International Publishing :2024. - viii, 187 p. :ill. (some col.), digital ;24 cm. - Engineering materials,1868-1212. - Engineering materials..

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.

This book addresses digitalization and the steel industry. It is written from the perspective of both industrial engineering and data science and discusses digitalization problems, novel production planning and scheduling algorithms in ironmaking and steelmaking, machine learning applications and opportunities in steel plants and quality-related algorithms in steel plants. Even though digitalization is an important trend in steel industry, current contributions mainly focus on lower automation levels, i.e., field and control levels, that are mainly covered in mechanical, electrical and material engineering domains. On higher planning levels, there are hardly comprehensive scientific contributions on intelligent digitalization issues available. This book fills this gap.

ISBN: 9783031574689$q(electronic bk.)

Standard No.: 10.1007/978-3-031-57468-9doiSubjects--Topical Terms:

969153
Steel industry and trade
--Technological innovations.

LC Class. No.: HD9510.5

Dewey Class. No.: 338.47669142

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505 0 $a 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.
520 $a This book addresses digitalization and the steel industry. It is written from the perspective of both industrial engineering and data science and discusses digitalization problems, novel production planning and scheduling algorithms in ironmaking and steelmaking, machine learning applications and opportunities in steel plants and quality-related algorithms in steel plants. Even though digitalization is an important trend in steel industry, current contributions mainly focus on lower automation levels, i.e., field and control levels, that are mainly covered in mechanical, electrical and material engineering domains. On higher planning levels, there are hardly comprehensive scientific contributions on intelligent digitalization issues available. This book fills this gap.
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