Leveraging digital twin-based simulation and artificial intelligence to advance sustainable manufacturing: a holistic approach to sustainability decision-making

This study explores the application of simulation-based digital twin technology, artificial intelligence and a sustainability impact analysis framework to facilitate informed sustainability decision-making in manufacturing. Through a case study at a UK-based manufacturing company, the authors modelled, analysed and optimised the manufacturing process for environmental, economic and social performance. The results reveal the interdependencies among energy consumption, productivity, employee motivation, and workplace hygiene. Based on these findings, the authors propose a comprehensive digital twin and AI-based framework. This framework aligns with life cycle sustainability analysis principles, enabling predictive and holistic decision-making in sustainable manufacturing.