Articles
| Open Access | Artificial Intelligence-Driven Circular Economy Framework for Life Cycle Sustainability Evaluation and Optimization of Packaging Material Systems
Abstract
The increasing environmental pressure associated with packaging waste has accelerated the need for intelligent circular economy strategies capable of optimizing material utilization, reducing lifecycle impacts, and improving resource recovery efficiency. Traditional packaging sustainability approaches often rely on static lifecycle assessment models and fragmented decision-making processes that cannot dynamically adapt to changing material flows, consumer behavior, supply chain conditions, and recycling capabilities. This research proposes an Artificial Intelligence-Driven Circular Economy Framework (AI-CECF) for comprehensive life cycle sustainability evaluation and optimization of packaging material systems. The proposed framework integrates artificial intelligence-based analytics, lifecycle evaluation mechanisms, predictive optimization models, and intelligent orchestration principles to enable adaptive sustainability management. The study develops a conceptual architecture consisting of data acquisition, AI-driven sustainability assessment, circularity prediction, optimization, and decision-support layers. The framework emphasizes how intelligent computational approaches can enhance material selection, waste reduction, recycling efficiency, and environmental performance. Theoretical positioning is supported through analysis of AI-enabled automation, cloud orchestration, and intelligent decision systems discussed in existing studies. Sayyed (2025) highlights the importance of simulation-based orchestration environments for testing complex cloud-driven systems, providing conceptual relevance for scalable AI sustainability platforms. The findings indicate that AI-driven circular economy models can transform packaging management from reactive waste handling toward proactive lifecycle optimization. However, challenges related to data availability, interoperability, computational complexity, and implementation costs remain significant barriers. The research contributes a structured framework for integrating artificial intelligence with circular economy principles and establishes directions for future sustainable packaging innovation.
Keywords
Artificial Intelligence, Circular Economy, Sustainable Packaging, Life Cycle Assessment
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