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August-Wilhelm Scheer Institut

R&D Institution

www.aws-institut.de/Saarbrücken, Germany

About

At the August-Wilhelm Scheer Institute, we are dedicated to advancing research and innovation in the fields of digitalization and business transformation. Our multidisciplinary team collaborates with industry partners and academia to develop cutting-edge solutions that address the challenges of the digital age. We place a strong emphasis on practical applications of our research, ensuring that our findings drive tangible benefits for businesses and society. Together, we strive to shape the future of digitalization and contribute to sustainable economic growth.

Data technologies, data ecosystems and cross-linking

Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems(AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths(AI based) process and system control technologies(AI based) Material and Product Design, Decomposition and SeparationSimulation models and predictive analytics to assess the scalability of circular processes across industriesAlgorithm that shows the (positive) impact of a Circular Economy process or Circular Economy productApproaches to support SME fully exploit the value of existing CVC-related dataDesign of an adaptable Digital Product Pass

Other 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)AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled componentsIndustry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains(Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurementRobotic / handling - and assistance systemsLife cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product PassportReverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)Network design of reverse supply chains

Representatives

Yajing Chen

Digitalization associate

August-Wilhelm Scheer Institut

Ann-Katrin Müller

Junior Researcher

August-Wilhelm Scheer Institut

Laura Bies

Lab Lead Smart Quality

August-Wilhelm Scheer Institut

Marketplace (2)

  • Project cooperation

    Looking for partners

    Digital Platform for Circular Textile Recycling in the EU

    • Early idea
    • Expertise offered
    • Consortium seeks Partners
    • Data technologies | (AI based) process and system control technologies
    • Data technologies | (AI based) Material and Product Design, Decomposition and Separation
    • 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 | 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.
    Author

    Laura Bies

    Lab Lead Smart Quality at August-Wilhelm Scheer Institut

    Saarbrücken, Germany

  • Expertise

    AI Expertise - Research

    Research institute focused on state-of-the-art AI research

    • Data ecosystems
    • Industry 4.0 technologies
    • (AI based) recognition systems
    • Manufacturing and machine learning
    • (AI based) Material and Product Design
    • Simulation models and predictive analytics
    • (AI based) process and system control technologies
    Author

    Laura Bies

    Lab Lead Smart Quality at August-Wilhelm Scheer Institut

    Saarbrücken, Germany