Assad, FadiPatsavellas, JohnSalonitis, Konstantinos2024-12-132024-12-132024-11Assad F, Patsavellas J, Salonitis K. (2024) Enhancing sustainability in manufacturing through cognitive digital twins powered by generative artificial intelligence. Procedia CIRP, Volume 130, November 2024, pp. 677-6822212-8271https://doi.org/10.1016/j.procir.2024.10.147https://dspace.lib.cranfield.ac.uk/handle/1826/2325957th CIRP Conference on Manufacturing Systems 2024, 29-31 May 2024, Póvoa de Varzim, PortugalThe rise of Industry 4.0 has brought new advancements in manufacturing, with a focus on integrating digital technologies to optimise processes and increase sustainability. Cognitive Digital Twins (CDTs) are emerging as a powerful paradigm in this area. They leverage advanced analytics, artificial intelligence (AI), and machine learning to create dynamic, real-time representations of physical manufacturing systems. This paper explores how CDTs can improve sustainability within the manufacturing sector. It proposes integrating generative artificial intelligence (GenAI) into the platforms that operate these digital twins to grant them cognitive capabilities. The work introduces a method for mapping and integrating energy consumption data to an Internet of Things (IoT) platform that includes the digital twin and a generative AI language model, such as ChatGPT. This proposed approach serves as a stepping stone towards unlocking the full potential of CDTs. It empowers manufacturers to achieve higher levels of sustainability and environmental responsibility.pp. 677-682enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/4014 Manufacturing Engineering40 EngineeringMachine Learning and Artificial IntelligenceNetworking and Information Technology R&D (NITRD)Data Science9 Industry, Innovation and Infrastructure4014 Manufacturing engineeringArticle559986130