Model based optimization tool (EAF_OPT) for enhancing Energy Efficiency, Productivity and Yield of Electric Arc Furnaces
Implementing Organization
Institute of Technology (IIT), Kanpur
Principal Investigator
Amarendra K Singh
Professor
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Department of Biological Sciences and Bioengineering, Indian Institute of Technology (IIT), Kanpur, Uttar Pradesh
Department of Materials Science and Engineering
CO-Principal Investigator
Dr. Dipak Mazumdar
Professor
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Department of Biological Sciences and Bioengineering, Indian Institute of Technology (IIT), Kanpur, Uttar Pradesh
Ministry Of Steel Chair Professor, Department of Materials Science & Engineering
Project Overview
Electric arc furnace (EAF) route accounts for nearly 25 % of steel produced in India. EAF units in India use variety of charge materials including large amount of hot-briquetted iron (HBI)/direct-reduced iron (DRI), pig iron, scrap and other raw materials and proportion of these raw materials to EAF vary substantially on account of availability and cost considerations of various components. Owing to the complex operations of EAF, commonly used static heat and mass balance based tools are incapable of providing optimal charge-mix leading to high energy consumption and loss of yield. A comprehensive dynamic model based tool, EAF_OPT, developed through this IMPRINT project, will assist steelmakers using EAF units of various sizes and capacities in optimizing charge-mix and charging sequence for improved energy efficiency, productivity and yield of their units.
Institute of Technology (IIT), Kanpur
Professor
Department of Materials Science and Engineering
Acces sibility Controls