Project cooperationUpdated on 27 May 2025
Circular product strategies via ultrasonic separation, automated condition analysis and lifecycle assessment of high-value components
About
The project aims to develop circular product strategies using ultrasonic-based separation and cleaning technologies for the recovery and reuse of high-value components. This is combined with automated condition assessment (e.g. via image processing) and digital data management to ensure traceability of materials and processes. A comprehensive assessment of energy use, CO₂ emissions, and cost enables comparison with conventional linear approaches. The approach is applicable across various sectors where critical raw materials and bonded multi-material assemblies pose recycling challenges.
Stage
- Early idea
Topic
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- 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)
Similar opportunities
Project cooperation
- Early idea
- Already defined
- Consortium seeks Partners
- Enabling technologies | Robotic / handling - and assistance systems
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- 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
Athina Kotrozou
Student
Stuttgart, Germany
Project cooperation
Al and Circular Economy in Coating and Insulation
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- 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
- 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 | 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.
Kaan AKSOY
Advanced Technologies and Sustainability R&D Department at BETEK BOYA VE KİMYA SANAYİ A.Ş
İSTANBUL, Türkiye
Project cooperation
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Enabling technologies | Robotic / handling - and assistance systems
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- 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
- 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.
Justus von Geibler
Co-Head Research Unit Innovation Labs at Wuppertal Institut für Klima, Umwelt, Energie
Wuppertal, Germany