RECYCLING AND REUSE OF MATERIALS IN METALLURGICAL PROCESSES

Abstract

The metallurgical recycling and reuse environment is rapidly evolving with digitalization, offering possibilities to improve metal recovery efficiency, traceability, and sustainability. As global raw material demand and eco-pressure rise, the use of digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), big data analytics, and digital twins is revolutionizing the way metallurgical industries manage waste, enhance recycling processes, and close material loops. In this study, the evolving role of digital technologies in supporting smarter and more responsive recycling systems in ferrous and non-ferrous metallurgy is investigated. Through an in-depth examination of existing practices, the study reveals how digital platforms are being utilized to track material flows, sort and separation procedures, and forecast equipment performance in real time. Data-driven sophisticated models are also facilitating improved decision-making in scrap classification, process control, and resource forecasting. Steel, aluminium, and electronic waste recycling case studies demonstrate how digitalization is unleashing added value from secondary raw materials, saving energy, and reducing greenhouse gas emissions. The research also addresses how the combination of Industry 4.0 technologies and circular economy thinking is driving a new era of intelligent metallurgical systems. Data interoperability issues, cybersecurity, and digital readiness of the workforce are also discussed. Through its multidisciplinary character, this study pinpoints the strategic value of digital innovation in supporting sustainable metallurgical processes. It provides valuable insights for industry players, policymakers, and academics who want to build more robust, efficient, and cleaner metal recycling systems.