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Project cooperationUpdated on 30 April 2025

Al and Circular Economy in Coating and Insulation

Kaan AKSOY

Advanced Technologies and Sustainability R&D Department at BETEK BOYA VE KİMYA SANAYİ A.Ş

İSTANBUL, Türkiye

About

As a leader in the paints and coatings industry, Betek Boya is committed to driving sustainability through bio-based solutions and circular economy principles.

Our Focus:

Bio-Based Coatings & Insulation: Developing high-performance paints and insulation materials derived from plant-based raw materials, reducing dependency on fossil fuels.
Circular Economy in Manufacturing: Minimizing waste, optimizing resource efficiency, and promoting recyclable/reusable materials in production.
Eco-Friendly Innovations: Creating durable, low-VOC, and sustainable coating solutions that support green construction and industrial applications.

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 | (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
  • 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 | Network design of reverse supply chains

Type

  • Consortium seeks Partners

Organisation

BETEK BOYA VE KİMYA SANAYİ A.Ş

University

İSTANBUL, Türkiye

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    • 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

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    • 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

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    London, United Kingdom

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    MAIUpcycle: Mainstreaming upcycling through the AI-assisted replication and scaling of upcycling stores in Europe

    • Already defined
    • Expertise offered
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    • 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