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Project cooperationUpdated on 20 August 2025

Use of the Asset Administration Shell to increase the degree of automation in the dismantling and reuse determination of battery-powered systems

Christian Schröder

Research Associate at Fraunhofer IWU

Chemnitz, Germany

About

The proposed project aims to promote the circular economy within the field of battery-powered systems. The goal is to enable the economic recycling of batteries in line with the circular economy and new business models. The project is divided into two key areas: designing battery systems for easy dismantling and verifying this through robot-assisted, automated dismantling; and determining the condition of individual battery system components for automatic decision-making on the recycling strategy.

The development of easy-to-disassemble designs is done in an agile approach by verifying each design concept by an automated robot-based disassembly. The robots program is therefore automatically generated from the disassembly instruction in the battery passport to avoid the manual, time-consuming task of robot programming. This makes the process economically efficient and resilient to a wide variety of design variants, enabling new business models.

The second key topic focuses on automatically deciding on a recycling strategy for battery system components, such as cells and electronics. Therefore, it is necessary to acquire data throughout the entire lifetime of the battery system. This includes, for example, state variables of battery cells during production, before packaging, and usage patterns when the system is in use. This data is gathered unambiguously for each battery system and depicted in a digital twin. A digital twin is created for each produced battery system using an asset administration shell, which is the Industry 4.0 standard for digital twins. This enables big data analytics. Closely related to this is the holistic assessment of reuse strategies. These are evaluated in terms of their ecological and economic impact.

Stage

  • Already defined

Topic

  • 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 | Design of an adaptable Digital Product Pass:

Type

  • Consortium seeks Partners

Organisation

Fraunhofer IWU

R&D Institution

Chemnitz, Germany

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    Adrian Barwasser

    Research Fellow at Fraunhofer IAO

    Stuttgart, Germany

  • Project cooperation

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    Tim Schnieders

    Researcher at WZL RWTH Aachen University

    Aachen, Germany

  • Expertise

    Adaptive Robotics for (Dis-)Assembly

    • Reverse Manufacturing
    • Industry 4.0 technologies
    • Manufacturing and machine learning
    • Robotic / handling - and assistance systems

    Ron Martin

    Group Manager Adaptive Robotics at Fraunhofer IIS, Division Engineering of Adaptive Systems

    Dresden, Germany