As the global population continues to rise, the pressure on natural resources increases, leading to extensive raw material extraction and growing volumes of waste. This results both exacerbate resource depletion including environmental degradation and contributes significantly to greenhouse gas emissions. The problem has become particularly evident in addressing the increasing raw material needs for renewable energy investments consisting of solar panels, wind turbines and batteries under limited and geographically constrained resources along with the end-of-life (EoL) management of retired systems. To address these interconnected issues, a transition toward a circular economy (CE) presents a promising path forward. CE emphasizes regenerative systems that extend product lifecycles through reuse, recycling, and resource recovery and helps to reduce dependency on virgin materials while managing waste more sustainably. However, achieving this transition is complex, requiring the alignment of environmental, economic, and social goals across various stakeholders, including industry, policymakers, and society. This necessity calls for advanced mathematical models to make informed investment, operations, and regulatory decisions.
This study presents a holistic Circular Economy Systems Engineering (CESE) framework, integrating multidisciplinary approaches to systematically design, operate, and optimize cost-effective, environmentally conscious, and resilient systems that close material and energy loops while addressing economic, environmental, and social objectives under resource constraints. To demonstrate the practical application of the framework, we present a case study on EoL management of monocrystalline silicon photovoltaic panels, combining cost and life-cycle assessment (LCA) driven CO2 equivalent emissions parameters in a mixed-integer linear programming (MILP) approach to evaluate trade-offs and identify optimal strategies for material recovery and waste reduction. The study reveals how the model can guide decision-makers in balancing economic viability with environmental responsibility, ultimately contributing to the development of circular supply chains. The findings highlight the potential of CE-driven optimization tools to recover critical materials and support long-term sustainability goals within complex forward and reverse supply chains
