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Project cooperationUpdated on 2 July 2025

Looking for a partner

Kyra Sophie Rimrodt

Fraunhofer Institute for Solar Energy Systems

Freiburg im Breisgau, Germany

About

Our vision is to improve resource efficiency during and after the product life cycle of a heat pump by closing the data gap between component ageing and the circularity of materials.

Goals

  • Develop a business model to enable data collection and circular value creation around heat-pump leasing models

  • Equip manufacturers and service providers for upcoming regulations (e.g., Digital Product Passport), while enabling cost-effective and resource-efficient operation through predictive maintenance

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 | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
  • Data technologies | Design of an adaptable Digital Product Pass:
  • 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) Materials and additive manufacturing
  • 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)

Type

  • Consortium seeks Partners

Organisation

Fraunhofer Institute for Solar Energy Systems

R&D Institution

Freiburg im Breisgau, Germany

Similar opportunities

  • Project cooperation

    Heat-as-a-service PLUS +

    • Early idea
    • Consortium seeks Partners
    • Data technologies | Design of an adaptable Digital Product Pass:
    • 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 | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.

    Sina Herceg

    Scientist at Fraunhofer Institute for Solar Energy Systems

    Freiburg im Breisgau, Germany

  • Project cooperation

    Euraka & Horizon Project Oppotunity

    • Early idea
    • Expertise offered
    • Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
    • Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components

    Hakan Bozcu

    Senior Innovation Projects Specialist at Eczacıbaşı Building Products

    Bilecik, Türkiye

  • Project cooperation

    Circular Adaptation for Road Vehicle Sustainability (CARS)

    • Early idea
    • Already defined
    • Consortium seeks Partners
    • Enabling technologies | Network design of reverse supply chains
    • Data technologies | (AI based) process and system control technologies
    • Data technologies | (AI based) Material and Product Design, Decomposition and Separation
    • Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
    • 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)
    • Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
    • 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 | 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)

    Alireza Ahmadi

    Professor-Operation and Maintenance Engineering at Luleå University of Technology-Division of Operation and Maintenance Engineering

    Luleå, Sweden