Project cooperationUpdated on 13 August 2025

AI, Digital Twin & Data-Driven Solutions for Circular Value Creation

Expert R&D Engineer at OBSS Technology

Istanbul, Türkiye

About

OBSS R&D Center brings over 20 years of experience and 1,000+ delivered projects in mission-critical software, AI, and simulation systems. We seek consortia for the Eureka Network “Circular Value Creation 2025” call to co-create scalable, data-driven solutions for sustainable production and resource optimization.

Our capabilities include:

AI & Data Analytics: Predictive maintenance, waste classification, material lifecycle optimization.
Digital Twin & Simulation: Virtual modelling of supply chains, process optimization, environmental impact assessment.
Computer Vision & IoT: Automated sorting, quality control, real-time operational feedback.
Cloud & Systems Integration: Secure, interoperable platforms enabling cross-sector collaboration.
Satellite & Drone Monitoring: Environmental compliance and resource mapping.

We can contribute as a technology partner providing end-to-end digital transformation, advanced analytics, and intelligent automation for circular economy initiatives.

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) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
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 | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
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 | Robotic / handling - and assistance systems
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 | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
Enabling technologies | Network design of reverse supply chains

Similar opportunities

Project cooperation
Reverse value chain for circular electronics management - supported by postal networks
- Early idea
- Already defined
- Consortium seeks Partners
- Enabling technologies | Network design of reverse supply chains
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- 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
- 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
Koeun Lee
Circular economy and value chains consultant at Universal Postal Union (UPU)
London, United Kingdom
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
Digital ecosystem for circular value creation
- Early idea
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- 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
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- 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 | 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)
Yoav Nahshon
Team Leader Materials Informatics at Fraunhofer IWM
Freiburg, Germany