Project cooperationUpdated on 7 September 2025
Digital ecosystem for circular value creation
About
The proposed project aims to deliver enabling technology that powers trusted digital platforms for secondary resources. By covering the complete supply chain and providing adjustable Digital Product Passports, the technology ensures interoperability across sectors while embedding quality assurance, environmental footprint transparency, digital twin simulations, and advanced matchmaking. The technology will be deployable through existing and new platforms, empowering industries and SMEs to accelerate the circular transition.
Stage
- Already defined
Topic
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Assistance and Expert systems
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
Type
- Consortium seeks Partners
Organisation
Similar opportunities
Project cooperation
Circular and Sustainable Transport Infrastructure
- Early idea
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Amir Garmabaki
Associate Prof. at Luleå University of Technology
Luleå, Sweden
Project cooperation
Partner with us in Advancing Sustainable Mobility using Real-Time Environmental Data
- Early idea
- Consortium seeks Partners
- Data technologies | (AI based) process and system control technologies
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
Rama Aditya Goparaju
Ecosystem Informatics Inc.
Milton, Canada
Project cooperation
LLM4CVC - AI based planning for automated disassembly
- Early idea
- Already defined
- Consortium seeks Partners
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | Robotic / handling - and assistance systems
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Tim Schnieders
Researcher at WZL RWTH Aachen University
Aachen, Germany