ExpertiseUpdated on 3 July 2025
AI Expertise - Research
About
The August-Wilhelm Scheer Institute brings in strong expertise in digital transformation, AI-based decision systems, and the development of data-driven platform solutions. Our role focuses on:
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Designing and implementing digital twins and intelligent platforms for circular economy applications
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Applying AI and data analytics to optimize recycling processes and material flows
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Developing interoperable, scalable IT architectures for sustainable and cross-sectoral solutions
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Bridging the gap between research and industry through user-centered innovation and applied research
With extensive experience in EU-funded innovation projects, we support the digital transition of industries toward sustainability and circularity.
Field
- (AI based) Material and Product Design
- (AI based) process and system control technologies
- (AI based) recognition systems
- Data ecosystems
- Industry 4.0 technologies
- Manufacturing and machine learning
- Simulation models and predictive analytics
Organisation
Similar opportunities
Expertise
AI and Robotics-Driven Lifecycle Management for Industrial Automation
- Data ecosystems
- Reverse Manufacturing
- Industry 4.0 technologies
- AI-driven diagnostic systems
- (AI based) recognition systems
- Manufacturing and machine learning
- Robotic / handling - and assistance systems
- Life cycle assessment / Product life cycle management
Vivek Chavan
Research Associate at Fraunhofer IPK
Berlin, Germany
Expertise
Senior Expert Sustainable and Circular Finance
- Data ecosystems
- (AI based) recognition systems
- Life cycle assessment / Product life cycle management
Carolina Andrén
Senior Expert Circular Finance at RISE Research Institutes of Sweden
Stockholm, Sweden
Project cooperation
- 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.
Laura Bies
Lab Lead Smart Quality at August-Wilhelm Scheer Institut
Saarbrücken, Germany