AI-driven digital circular economy with material and energy sustainability for industry 4.0

Abstract

Circular Economy and Sustainability in Industry 4.0 Era are promoters for carbon neutrality transformation, while their interconnected nexus and specific roles in low-carbon transition have not been clearly revealed. Furthermore, an integrated circular economy framework with buildings, PVs, battery and EVs, with overlaps in renewable-driven operational stages has not been considered in lifecycle decarbonization. This study is to reveal the nexus between Circular Economy and Sustainability in Industry 4.0 Era. Operational modes and mechanism of Circular Economy in PVs, buildings, electric vehicle industries and batteries are specifically analysed, together with energy and carbon flow analysis and optimization. Roles of Circular Economy in Sustainability have been provided, through an integrated circular economy framework with buildings, PVs, battery and electric vehicles (EVs), considering the overlap in renewable-energy driven operational stages in lifecycle decarbonization. Last but not the least, waste material recovery and waste-to-energy conversion have been analysed within the close-in-loop cycle for sustainability transition. Advanced digital technology in future Circular Economy is formulated with data-driven circular economy and internet-of-thing (IoT)-based waste-to-energy framework. Research results indicate that circular economy plays significant roles in sustainability, including cascade reuse paradigm, reverse supply chain with the recovery of end-of-life batteries, EV lifetime extension via repair and reuse, low carbon with refurbishing and remanufacturing, and less new primary materials via recycling materials, waste material recovery and waste-to-energy conversion. The renewable-driven battery-building-transportation-waste circular economy chain with the cross overlap in clean energy utilization can partially offset carbon emissions during the raw materials mining, manufacturing and recycling stages. This study can promote the waste to energy and advanced machine learning techniques with Circular Economy and Sustainability in Industry 4.0 Era.