Remanufacturing scheme design (RSD) is an essential step in the restoration and upgrading of used products. However, the quantity of remanufactured products is growing rapidly, and customers have personalized demands for remanufactured products that lead to shorter design cycles. In addition, the used products are scrapped due to their own defects, such as performance failure and functional degradation, which correspond to the inherent remanufacturing demand (IRD) of used products. Faced with large quantities of used products, how to quickly develop reasonable remanufacturing schemes for satisfying customers’ individual demands and the IRD is an urgent problem to be solved. To address these issues, a mass customization-based RSD method is proposed. First, remanufacturing demand comprising customer demand and the IRD is analyzed to determine the RSD targets and remanufacturing types. Then, the RSD methods are intelligently selected based on the remanufacturing types, which include restorative remanufacturing, upgrade remanufacturing and hybrid remanufacturing, while the hybrid contains restorative remanufacturing and upgrade remanufacturing. Moreover, the restorative remanufacturing scheme is generated to satisfy the restorative remanufacturing targets based on reverse engineering (RE) and the tool contact point path section line (TCPPSL) method. After used products are restored, case-based reasoning (CBR) is used to retrieve the case that best matches the upgrade remanufacturing targets, while the grey relational analysis (GRA) algorithm is applied to calculate the similarity between cases. Finally, the feasibility of this method is verified by considering the RSD of a used lathe. The results indicated that the proposed approach can rapidly help designers to obtain remanufacturing solutions for satisfying the customer demand and IRD.

Rapid urbanization and climate change have intensified environmental pressures and social inequalities, making the integration of urban resilience and sustainable development a critical global challenge, with Nature-based Solutions (NbS) emerging as a promising pathway; however, the knowledge structure, collaboration patterns, and evolutionary trends of NbS research remain fragmented and insufficiently understood. This study conducts a comprehensive bibliometric analysis of 1261 publications from the Web of Science Core Collection (2005–2025), employing tools including VOSviewer 1.6.20, CiteSpace 6.4.R1, and Bibliometrix 4.1.3 to map publication trends, collaboration networks, knowledge bases, and thematic evolution. The results reveal a rapid expansion of NbS research since 2013, characterized by strong interdisciplinarity and a multicentric yet uneven geographical distribution dominated by China, the United States, and Europe. Four major research clusters are identified, encompassing policy governance, environmental benefits, ecosystem services, and social equity, reflecting a shift from ecological performance to integrated socio-ecological frameworks. Additionally, thematic evolution indicates growing emphasis on governance mechanisms, public health, and environmental justice. Overall, NbS research is transitioning toward a multi-scale, multi-objective, and governance-oriented paradigm. These findings highlight the need for strengthened international collaboration, standardized evaluation frameworks, and inclusive policy design to enhance the effectiveness and global applicability of NbS in advancing urban sustainable development.