Intelligent Life Cycle Assessment Model for Sustainable Packaging Design Through AI-Based Circularity Analysis and Resource Efficiency Mapping
Keywords:
Artificial Intelligence, Life Cycle Assessment, Sustainable Packaging, Circular EconomyAbstract
The increasing complexity of global packaging systems has intensified the need for intelligent approaches capable of balancing environmental sustainability, material efficiency, and circular economy objectives. Traditional Life Cycle Assessment (LCA) approaches often face limitations in dynamic data processing, real-time decision support, and integration with emerging digital technologies. This research proposes an Intelligent Life Cycle Assessment Model for Sustainable Packaging Design Through AI-Based Circularity Analysis and Resource Efficiency Mapping, integrating artificial intelligence (AI), circularity evaluation mechanisms, and resource optimization techniques into a unified analytical framework. The proposed model employs AI-driven data interpretation, lifecycle impact prediction, material flow assessment, and resource efficiency mapping to support sustainable packaging decisions across design, production, utilization, and end-of-life stages. The conceptual framework incorporates principles from intelligent automation, digital simulation, and compliance-oriented analytical systems. Existing research on AI-enabled decision systems, secure digital ecosystems, automation frameworks, and computational modeling provides theoretical foundations for developing adaptive sustainability assessment mechanisms. The findings indicate that AI-enhanced LCA models can improve environmental impact visibility, identify circularity opportunities, and support evidence-based packaging innovation. However, challenges related to data quality, computational complexity, interoperability, and regulatory alignment remain significant barriers. The study contributes a conceptual pathway for integrating AI intelligence with lifecycle sustainability analysis to enable next-generation packaging systems.
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