Material Sciences

Title :

Model based optimization tool (EAF_OPT) for enhancing Energy Efficiency, Productivity and Yield of Electric Arc Furnaces

Area of research :

Material Sciences, Energy Sciences

Focus area :

Material processing technologies

Principal Investigator :

Amarendra K Singh, Professor, Department of Materials Science and Engineering, Indian Institute of Technology (IIT), Kanpur


Executive Summary :

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.


Dr. Dipak Mazumdar, Professor, Ministry Of Steel Chair Professor, Department of Materials Science & Engineering, Indian Institute of Technology (IIT), Kanpur

Total Budget (INR):


Organizations involved