The Application of AI for Electronic LCA Data and Assessment Toward the Circular Economy

LCA is viewed as one of the important techniques to assess the environmental impacts of products, especially during the whole of the life cycle towards a circular economy approach. In the electronics sector, where products undergo rapid technological advancements and complex supply chains, LCA plays a crucial role in promoting sustainability and guiding decision-making processes. On the one hand, the environmental sustainability of electronics like ICT, Consumer Electronics, micro-electronics and Network Equipment is affected by the huge missing data because of the complexity, variety, large number of components, and otherwise different suppliers around the world. A more accurate, reliable, and standard LCA data management is necessary to decrease risks in the Supply Chain, increase transparency and provide sustainable and circular Business Models for Electronic Products and ICT Services. Meanwhile, artificial intelligence (AI), and particularly the advances in machine learning (ML) and deep learning (DL) have led to disruptive innovations in data modeling and other fields. To address this issue in the electronic industry, the integration of big data and artificial intelligence (AI) can transform precision assessment from data inventory to automated LCA modeling, and innovative methodologies for a cost-efficient data configuration. We provide a comprehensive overview of advances in the application of big data and AI technologies for LCA of electronics. We discuss key challenges in missing data and utilization for electronics and micro-electronics, offering strategic solutions. This novel AI-data approach helps organizations easily provide the missing data by integrating complex and disparate data sources across multiple distributed sources to give insights. Meanwhile, a dynamic big data discovery approach delivers more accurate and precious data for intelligent decisions. The intention is to provide the industry, LCA experts, and decision-makers with a more standardized, comprehensive, and reliable data ecosystem. (Abstract)