CIRCE – Circular Product Creation | Circular product development through the integration of remanufacturing and product generation development using digital product instances

EFRE-Innovation Network CIRCE – Circular Product Creation

Resource consumption in German industry significantly exceeds sustainable limits, primarily due to a linear economic model characterized by high demand for primary raw materials and substantial waste volumes. The circular economy model counters this with closed-loop material cycles in which products and components are used for as long as possible. Remanufacturing - the reuse of used components - plays a central role in this context. While remanufacturing is well-established in capital-intensive industries, obstacles remain in mechanical engineering and in the electrical and electronic equipment sectors, such as a high variety of product variants, uncertain return-quality standards, and a low level of digitalization. The goal of the innovation network is to significantly increase the reuse of used components in new product generations. At its core is the digital integration of recovery, reverse engineering, and product development based on digital product instances. AI-based methods support the management of uncertainties regarding the quantity, geometry, and condition of the components. To this end, new approaches are being developed for reverse engineering, circular supply chains, flexible disassembly and inspection processes, as well as additive manufacturing processes. The resulting end-to-end process chain enables cost-effective remanufacturing, particularly for small and medium-sized enterprises, and contributes to resource conservation.

Partial project TU Clausthal: CIRCE-TUC

AI-based condition assessment, digital remodeling, and Design Automation process for integrating used components into new products.

Initial situation and problem definition

In industrial practice, the reuse of used components often fails due to insufficient information about their geometry, functionality, and condition. Particularly for products with a high degree of variation, there is a lack of standardized procedures for identifying suitable components at an early stage and systematically evaluating their potential for reuse. Existing approaches usually require a significant amount of manual effort and yield results with limited transferability. Furthermore, relevant information is fragmented throughout the process and not consistently available. This makes efficient planning of disassembly, evaluation, and integration difficult, and the existing potential for reuse remains largely untapped.

Project goals

The goal of the partial project at Clausthal University of Technology is to develop digitally supported methods for identifying, evaluating, and utilizing used components in the context of product generation development. The focus is on the automated capture of geometric and condition data using sensor technology and artificial intelligence, as well as making this data available in the form of digital product instances. To enable the targeted reuse of components, research will focus on development methods that allow for the reactive adaptation of new product generations to available components. In addition, methods for performance evaluation and for supporting disassembly and development decisions will be developed. Overall, the goal is to increase reuse rates and reduce development costs through partially automated, flexible process chains.

Solution approach pursued

The solution combines sensor-based data collection, AI-driven analysis, and product generation development into an integrated process chain. Imaging techniques such as 3D scanning, as well as thermographic and spectral analyses, capture the geometric and condition characteristics of used components. AI models support the classification, feature extraction, and assessment of reuse potential. The information is structured into digital product instances and made available for downstream processes. Building on this, product generation development is specifically expanded: New product generations are not designed exclusively based on ideal new parts, but are reactively adapted to available used components. Design Automation approaches are intended to enable the automated generation of necessary interface, structural, and adaptation components and their design for manufacturing, including for innovative additive manufacturing processes such as non-planar 3D printing. The methods are validated using demonstrators and transferred to real-world applications in collaboration with industry partners.

Funding information

The CIRCE Innovation Network is funded by „Europäischen Fonds für Regionale Entwicklung“ (EFRE) and the State of Lower Saxony, program area „Stärker entwickelte Region“ (SER) funded. The subproject at Clausthal University of Technology is receiving 782,000 € in funding.