The increasing urgency of climate change mitigation has intensified the need for sustainable and carbon-neutral manufacturing systems. While Industry 4.0 technologies have transformed industrial operations through enhanced automation, connectivity, and intelligence, significant challenges remain in integrating operational optimisation with environmental sustainability objectives. This study proposes an AI-integrated digital twin framework designed to support carbon-neutral smart manufacturing through real-time monitoring, predictive analytics, and life cycle assessment (LCA)-based environmental evaluation. The proposed framework combines Internet of Things-enabled data acquisition, digital twin technology, machine learning algorithms, and sustainability assessment tools within a unified decision-support architecture. Artificial intelligence models are employed for predictive maintenance, energy consumption forecasting, and production scheduling optimisation, while the digital twin provides continuous synchronisation between physical manufacturing assets and their virtual counterparts. To evaluate environmental performance, a life cycle assessment framework is integrated into the system to quantify carbon emissions and assess sustainability impacts throughout manufacturing operations. Results from the case study analysis indicate that the proposed framework improves operational efficiency by reducing equipment downtime, optimising energy use, and enhancing production throughput. Furthermore, the integration of AI-driven optimisation and digital twin technologies contributes to significant reductions in carbon emissions and environmental impacts across multiple life cycle categories. The findings demonstrate that the convergence of artificial intelligence, digital twins, and LCA can provide an effective pathway toward carbon-neutral manufacturing by enabling data-driven decision-making and continuous sustainability optimisation. This study adds to the expanding body of literature on Industry 4.0 sustainability by introducing an integrated framework that connects intelligent manufacturing systems with environmental performance management.
Keywords: artificial intelligence, digital twin, Industry 4.0, smart manufacturing, carbon-neutral manufacturing, life cycle assessment, sustainability, predictive maintenance, energy optimisation, industrial decarbonisation