The development of secondary sources as industrial feedstocks is important to creating resilient supply chains that contribute towards diverting resources away from landfills, mitigating deleterious environmental impacts, and minimizing market volatility. A major challenge to develop secondary feedstocks is the coordination and digitalization of the large quantities of generated information at each phase of a product’s life cycle. This paper builds upon earlier work that illustrates a top-level model of the activities and information needs to integrate product manufacturing with circular practices. This paper extends the initial work to explore the cyclical nature of Circular Economy (CE) information flows specifically related to product End-of-life. Using the Integrated Definition 0, IDEF0, modeling technique this paper examines the End-of-life function envisioned under a CE manufacturing model [ISO, 2012]. This function is decomposed into subsequent child functions and is analyzed relative to other product life cycle phases. The paper reviews the current global product EoL practices and in the context of the developed IDEF0 model. The proposed framework contributes a detailed description and presentation of information flows and the drivers of change (i.e., feedback loops) that are essential for creating secondary material streams based on the critically analyzing the reviewed literature. The novelty of this study includes the identification of standards and metrics gaps to facilitate quantitative assessment and evaluation in a CE. The study further elucidates the discussion around CE in terms of resource regeneration by ‘designing out waste’ and decoupling economic growth from resource depletion.

Global population growth and increasing resource scarcity are necessitating sustainable manufacturing and circular economy (CE) practices. These practices require the decisions made at each product life cycle (PLC) stage consider sustainability and circularity implications. We propose PLC system level optimization to identify the most favorable choices, instead of siloed individual PLC stage-specific optimizations. This should yield better circularity by permitting manufacturers to take a more holistic view and identify the areas of highest impact across the PLC. This paper presents initial work towards building a PLC system optimization framework. From an initial review of current circularity metrics, we identify metrics that are suitable for forming the optimization objectives. Second, we identify decision variables available to manufacturers across the PLC that are useful in optimizing the entire system’s circularity and sustainability. Finally, we identify limitations of current metrics, and discuss major challenges and potential solutions to PLC system optimization problems.

Closed-loop recycling streams are increasingly taking importance on the development of a sustainable future. Neodymium-iron-boron (Nd-Fe-B) permanent magnets are applied in a variety of applications, including direct-drive wind turbines, electric motors for electric vehicles, hard disk drives (HDDs) in laptops, and other electric devices. End-of-life HDDs are available in the United States to be collected and recycled for the production of Nd-Fe-B magnets for the exponentially increasing demand in electric vehicles and other industries. A comparative assessment of the environmental impact of HDD recycling pathways is conducted for the production of Nd-Fe-B magnets in the United States. The results show that the magnet-to-magnet recycling route has the lowest footprint. A techno-economic assessment is conducted to compare the added value of a harvesting process versus shredding HDDs. After conducting an uncertainty analysis with an optimization technique, multiple scenarios for a harvesting facility are economically feasible. Future work will be needed to reduce financial risks.

Gallium, Indium and Cobalt are critical materials that are vital to ramping up the adoption of clean energy technologies such as solar photovoltaics (PVs), electric vehicles (EVs) and wind turbines (WTs). Like other critical materials, they are prone to supply chain risks resulting in future uncertainty associated with supply, demand and price parameters. Understanding current and future market dynamics will mitigate this uncertainty. This article applies the Bass Diffusion Model to generate demand projections as three data sets each for Gallium, Indium and Cobalt until 2050. Generating and compiling these data are one step in enabling insights on future market parameters of the considered materials and the clean energy products that rely on their availability. Going forward this data has the potential to contribute towards understanding other market parameters such as supply and prices.