Industry 5.0's LLM-driven Technologies: A Prospect for Sustainable Production

Abstract

In the rapidly evolving landscape of manufacturing, the integration of Large Language Models has emerged as a promising approach to enhance sustainability and operational efficiency. As Industry 5.0 shifts its focus from automation and smart technologies to the cobots, augmented intelligence etc., there is tremendous improvement in the experience of manufacturing processes. One of the key areas where LLM-driven technologies can unlock the potential of Industry 5.0 is in the realm of fault detection and prediction. By leveraging the power of AI/ML, manufacturers can identify and address faults in real-time, leading to reduced waste, improved resource utilization, decision-making, and process automation. This paper explores the role of LLM in improving the efficiency of global industrial processes, achievement of sustainable and customizable industrial practices. A discussion about the challenges of application of LLM in supply chain optimization, process automation, and waste reduction to the support in energy management is provided. A case study of LLM aid in sustainable manufacturing across retail industry and steel industry is also presented.