Generative AI vs. Traditional Machine Learning for Energy-Efficient and Circular Manufacturing in Industry 5.0: A Life-Cycle-Based Framework for Sustainable Manufacturing

Abstract

This study proposes an integrated Industry 5.0 framework that compares and combines generative artificial intelligence (GenAI) with traditional machine learning (ML) to enhance the sustainability of manufacturing systems. This framework supports energy-efficient process optimisation, waste minimisation, material recycling and environmentally friendly production planning through data-driven decision-making. GenAI is more commonly used to generate sustainable process configurations and alternative eco-design solutions, whilst traditional ML models predict energy consumption, emissions and material losses in real time. It is proposed that a life cycle assessment (LCA) be carried out to estimate the environmental impact at all stages of production. Preliminary analyses indicate significant potential for reducing resource consumption, improving the circular economy, and supporting more sustainable and resilient manufacturing ecosystems and supply chains.