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Vivek Chavan

Research Associate

Fraunhofer IPK

Berlin, Germany

41 profile visits

My organisation

Fraunhofer IPK

Fraunhofer IPK

R&D Institution

Berlin, Germany

Fraunhofer IPK provides comprehensive support to companies from product development, planning and control of machines and systems, including technologies for parts manufacturing, to comprehensive automation and management of factory operations. We also transfer production engineering solutions to areas of application outside industry, such as traffic and safety. As an institute of the Fraunhofer-Gesellschaft, we tailor our work to fit the needs and requirements of our customers and partners. With its market orientation and high real-world value, our R & D helps to sharpen their long-term competitive edge. We develop forward-looking novel solutions and modernize, optimize and upgrade existing technologies and applications. At Fraunhofer IPK, we are realizing the vision of a complete digitalization of product development and planning processes – so that you as a manufacturer or user can consider the later phases of your product's life cycle at an early stage. In Digital Engineering, we are advancing innovative solutions along the dimensions of intelligent integration, to design individually and efficiently adapted and interoperable IT systems landscapes, sustainable product ecosystems, to consider, model and assess global interconnections of systems and their environment, as well as the extended reality, to create interactive, user-centered immersive environments in an engineering metaverse.
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About me

Interests

  • AI
  • computer vision
  • Industrial automation
  • Robotics
  • Machine Learning
  • reverse logistics

Marketplace (2)

  • Expertise

    AI and Robotics-Driven Lifecycle Management for Industrial Automation

    We’re building an AI-driven framework using vision, robotics & digital twins for smart sorting, disassembly, repair & reuse of products

    • 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
    Author

    Vivek Chavan

    Research Associate at Fraunhofer IPK

    Berlin, Germany

  • Project cooperation

    Driving Circular Value Creation in the White Goods Industry via Lifecycle Management and AI-driven 9Rs

    Goal: Unlock circular value in the white goods industry with AI and DPP. Seeking OEM, remanufacturing & tech partners in industry/academia.

    • Early idea
    • Already defined
    • Consortium seeks Partners
    • Data technologies | Assistance and Expert systems
    • Data technologies | Design of an adaptable Digital Product Pass:
    • Enabling technologies | Robotic / handling - and assistance systems
    • Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
    • 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 | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
    • 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
    • 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)
    Author

    Vivek Chavan

    Research Associate at Fraunhofer IPK

    Berlin, Germany