Revolutionising the Sustainability of Steel Manufacturing Using Computer Vision

Abstract

The pressure of the global sustainability problem is growing faster than ever after the social and economic havoc wreaked by the pandemic, as well as the present time nearing to the 2050 net zero carbon goal. In 2021 the steel industry had a turnover of around €125 billion and was directly responsible for providing at least 300000 jobs. In 2022, it was responsible for roughly 5% of CO2 emissions in the EU and 7% globally, and was responsible for at least 20278 injuries and 90 deaths. Environmental solutions for mitigating negative consequences of the steel industry exist such as hydrogen-based steelmaking, carbon capture, utilisation and storage and electrolysis, whilst safety regulations and personal protective equipment have been used to improve safety. However, little has been done to combat the problem using the most powerful emerging technology of the fourth industrial revolution, artificial intelligence. In particular, computer vision has already shown great competence in a range of applications related to steelmaking, but without seriously considering sustainability, resulting in limited awareness of the potential benefits computer vision can bring to industry. A lack of this awareness leads to missed opportunities for sustainable development. This paper aims to address the gap in research that discusses computer vision capabilities for enhancing the sustainability of steel production by providing a literature review covering recent advances in computer vision, as well as an industry 4.0 approach for integrating computer vision systems with steelworks. Research presented here successfully exposes the untapped potential of computer vision in the steel industry and paves the way for future developments by exhibiting a blueprint for simultaneously elevating sustainability and technological advancement.