Nigerian Engineer Highlights AI’s Role in Transforming Global Steel Industry
Experts have said the global steel industry is undergoing a significant transformation as artificial intelligence (AI) and machine learning (ML) increasingly shape manufacturing processed. Johnson Sunday Alabi, a Fellow of the Nigerian Institution of Professional Engineers and Scientists (NIPES) and a PhD candidate at Missouri University of Science and Technology, explained that AI is no […]
Experts have said the global steel industry is undergoing a significant transformation as artificial intelligence (AI) and machine learning (ML) increasingly shape manufacturing processed.
Johnson Sunday Alabi, a Fellow of the Nigerian Institution of Professional Engineers and Scientists (NIPES) and a PhD candidate at Missouri University of Science and Technology, explained that AI is no longer a futuristic concept but is steadily becoming central to modern metallurgy. According to him, both developing and developed countries need to integrate AI and data-driven systems into steel production to remain competitive.
Alabi noted that steel remains the backbone of global infrastructure, including bridges, buildings, vehicles, and power grids.
Yet, he said, its production continues to rely on traditional, energy-intensive methods guided largely by operator experience and fixed settings.
AI, he explained, differs because it combines physics-based modelling with machine learning to create “smart systems” capable of predicting real-time thermal and metallurgical responses, optimising process parameters, and reducing waste, emissions, and downtime.
He described a future scenario in which steel rolling lines could adapt operations for each bar or coil based on patterns learned from thousands of prior examples, rather than following a fixed recipe.
Highlighting the shift from traditional methods to intelligent automation, Alabi said AI-powered forecasting can predict equipment failures before they occur, while process optimisation software can analyse large volumes of data to ensure consistent product quality. He also pointed to the use of digital twins—virtual replicas of production lines—that allow rapid testing without waste, and AI-based quality control systems using computer vision to detect defects in real time.
On a global scale, Alabi observed, countries like the USA, Germany, Japan, and China are heavily investing in AI-driven predictive analysis, digital twins, and quality control systems. For emerging economies such as Nigeria, he said, the adoption of AI in steel manufacturing is both an opportunity and a strategic necessity. He urged local industries to “build smart from day one” by deploying AI-driven furnaces, adaptive energy management platforms, and modern quality control systems.
Alabi stressed that AI would not replace metallurgists, engineers, or plant managers but would enhance their capabilities by providing sharper tools, real-time feedback, and better insights. He added that, in a world where efficiency, precision, and sustainability are critical, artificial intelligence is “not optional but required.”
He concluded by expressing hope that his ongoing research in steel heat treatment, process optimisation, and decarbonisation will not only produce academic papers but also practical systems that could reshape steel manufacturing and the application of technology for industry and the environment.