Project cooperationUpdated on 1 July 2025
Smart & Circular Photovoltaic-Thermal Systems
About
Develop modular, recyclable photovoltaic (PV/ PVT) systems designed for seamless disassembly, integrated with digital tracking (tags, sensors) and lifecycle transparency (digital material passports + automated EPD generation). Systems will monitor performance and material condition through digital twins, optimizing reuse and recycling and enabling smart circular business models and environmental certifications.
Stage
- Early idea
- Already defined
Topic
- 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 | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
Type
- Consortium seeks Partners
Organisation
Similar opportunities
Project cooperation
- Early idea
- Already defined
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | Robotic / handling - and assistance systems
- 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
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- 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)
Vivek Chavan
Research Associate at Fraunhofer IPK
Berlin, Germany
Project cooperation
X-Ray Company to Identify Food Waste Within Bags in MRF - Stockholm
- Already defined
- Consortium seeks Partners
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
Hossein Shahrokni
Director of Research at LocalLife Sweden
Stockholm, Sweden
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