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September 13, 2024

Automating the Dismantling Process: Innovations from the FREE4LIB Project

As lithium-ion batteries (LIB) become increasingly common in various devices, the need for efficient recycling strategies grows. When these batteries reach the end of their life cycle, it is crucial to dismantle, pretreat, and classify them properly to safely extract valuable materials and minimize environmental impact. The FREE4LIB project aims to address the rising demand for efficient and safe processes for dismantling and classifying EOL LIBs. With the exponential increase in LIB usage across different sectors, there is a heightened concern regarding the proper handling of these batteries at the end of their life cycle.

Automating the dismantling process offers several key benefits:
Efficiency: Automation can significantly enhance the speed and accuracy of the dismantling process, ensuring precise and non-destructive extraction of valuable materials.
Safety: Automated systems reduce the risk to human operators by minimizing direct contact with hazardous and high-energy components, thus reducing the chances of accidents like fires or explosions.
Environmental Impact: Efficient and precise dismantling minimizes waste and maximizes the recovery of recyclable materials, contributing to more sustainable resource management.
The robotic disassembly of EV batteries presents significant challenges due to the lack of standardization in battery design and structure. Each battery is unique, requiring robots to continuously adapt to different designs and conditions and use advanced technologies like artificial vision to achieve precise dismantling. This challenge and opportunity have been extensively explored in our article, "Robotised Disassembly of Electric VehicleBatteries: A Systematic Literature Review," published by Tero Kaarlela, Enrico Villagrossi, Alireza Rastegarpanah, Alberto San-Miguel-Tello,and Tomi Pitkäaho. The development of robotic technologies for battery dismantling represents an opportunity to improve resource management by increasing efficiency, reducing environmental impact, and enhancing safety.

Results and Findings from FREE4LIB

The FREE4LIB project focuses on developing advanced robotic solutions for the sustainable and efficient dismantling of EOL lithium-ion batteries. By emphasizing robotic automation, the project aims to maximize material recovery efficiency. The main results and progress to be achieved are:
- Technological Innovations in Robotic Dismantling: Eurecat's Robotics and Automation Technology Unit has been at the forefront of researching and developing automated battery dismantling technologies. Our published article emphasizes the significance of these innovations in facilitating the safe extraction ofvaluable materials while minimizing environmental impact.
Challenges in Robotized Disassembly: The lack of standardization in EV battery design poses a significant challenge. Each battery is unique, necessitating robots to adapt to varying designs and conditions.
Collaborative Robotic Solutions: Eurecat has developed a collaborative robotic solution that allows human operators to perform high-value tasks alongside robots, enhancing overall efficiency and safety. These robots are equipped with custom tools that allow them to perform the appropriate operations. The work done by Eurecat includes:
o  Screw Detection and Unscrewing: Using a trained YOLO model, the robot detects the screws and moves to their positions, unscrewing them with a screwdriver tool. This technique is used to remove the external screws of the lid and the internal screws of the different battery packs, allowing the robot to perform repetitive unscrewing operations efficiently.
o  Lid Removal: Once the external lid is free of screws, a custom foam gripper tool adapts to the surface and manipulates it. In this stage, the robot performs handling operations of heavy and voluminous objects, ensuring safe and precise lid removal.
Advanced Control and Planning Systems: The robots utilize a behavior treel ibrary developed by Eurecat for task planning that enables dynamic and efficient handling of the dismantling process.

Commercial Applications and Future Upscaling

The findings and technologies developed through FREE4LIB have significant commercial potential and implications for upscaling:
Commercial Use: The robotic dismantling solutions developed can be commercialized to meet the growing demand for efficient battery recycling. We plan to offer these technologies through direct services and collaborations with recycling companies, enabling them to automate their battery dismantling processes, improve recycling efficiency, reduce operational costs, and enhance safety.
Upscaling FREE4LIBTechnology: The developed robotic system is designed to be adaptable for various battery models, enabling it to handle different types of batteries without needing predefined information such as CAD models. This flexibility ensures that the technology remains effective and relevant as battery designs and recycling needs evolve. Beyond battery dismantling, the solution can be extended to other dismantling scenarios, making it a versatile solution for various recycling applications.
Implementation Strategy: As a technological center, Eurecat will implement this Key Exploitable Result (KER) through several strategic initiatives. We plan to integrate the developed technologies into ongoing and future projects, advance the station's capabilities, and form collaborative partnerships with industry and research institutions. These efforts will drive innovation and the joint development of new applications.

Showcasing Advanced Robotic Solutions for Battery Dismantling

The expected results and work done on this project were showcased at the workshop "Facing the New Era of Transportation: Processing of EV Batteries" during the European Robotics Forum 2024 in Rimini. Attended by over 1,000 people, the workshop focused on the feasibility of AI and robotics for the disassembly of EV batteries. The discussions centered on advanced robotic solutions for autonomous disassembly, including the role of machine learning and digital twins in optimizing the process, the use of XR technology for robotic operator training, and the importance of task and motion planning to manage battery variability. The insights and findings from our published research provided a robust foundation for these discussions, underscoring the critical advancements made by the FREE4LIB project.

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