03535nam a22005175i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072002300183072001500206245014000221250001800361264007500379300006600454336002600520337002600546338003600572347002400608490003800632505078000670520078401450650001202234650002802246650002802274650001502302650002402317650002302341650004302364650002702407650002402434700014302458700008002601700008402681710003402765773002602799776003602825776003602861776003602897830003802933856004602971978-3-031-57468-9DE-He21320251030112611.0cr nn 008mamaa240703s2024 sz | s |||| 0|eng d a97830315746897 a10.1007/978-3-031-57468-92doi 4aTA459-492 7aTGM2bicssc 7aTEC0210302bisacsh 7aTGM2thema10aSteel 4.0h[electronic resource] :bDigitalization in Steel Industry /cedited by Yilmaz Uygun, Atilla Özgür, Marc-Thorsten Hütt. a1st ed. 2024. 1aCham :bSpringer International Publishing :bImprint: Springer,c2024. aVIII, 187 p. 92 illus., 54 illus. in color.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aEngineering Materials,x1868-12120 aIntroduction -- 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. aThis 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. 0aMetals. 0aIndustrial engineering. 0aProduction engineering. 0aMaterials. 0aBuilding materials.14aMetals and Alloys.24aIndustrial and Production Engineering.24aMaterials Engineering.24aSteel, Light Metal.1 aUygun, Yilmaz.eeditor.0(orcid)0000-0003-1271-96721https://orcid.org/0000-0003-1271-96724edt4http://id.loc.gov/vocabulary/relators/edt1 aÖzgür, Atilla.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aHütt, Marc-Thorsten.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303157467208iPrinted edition:z978303157469608iPrinted edition:z9783031574702 0aEngineering Materials,x1868-121240uhttps://doi.org/10.1007/978-3-031-57468-9