Automated Production Systems: Autonomous Disassembly
Project challenges
The exponential growth of EV adoption drives demand for critical battery materials like Cobalt and Nickel. Automated disassembly is key to efficient, high-value recycling.
Business challenge
Process Innovation
Sector
Electrification
Technology or capability
Automation & Robotics
Digital Manufacturing
Autonomous robotics for recycling of battery packs
MTC developed and demonstrated a machine vision led, autonomous task planner deployed on an industrial robot for the automatic detection and unfastening of bolts on complex assemblies, like battery packs. The developed architecture deals with the variation found in end-of-life vehicle battery packs and will underpin future research in battery pack disassembly.
Developing highly automated, high-throughput disassembly technology is critical in enabling a circular materials supply chain for battery-related critical materials in the UK.
Dan Fung, Head of Strategy and Performance, Advanced Propulsion Centre
The Challenge
Adoption of Electric Vehicles is increasing exponentially, pushing up demand for critical raw materials found in batteries such as Cobalt and Nickel. The value of the materials in end-of-life EV batteries in the UK will increase to more than £1bn by 2035. Efficiently recovering those critical raw materials at the highest yield whilst maintaining the highest possible value form is a global priority.
Disassembly has been shown to produce better quality recycled battery materials than direct shredding but is difficult in practice due to the complexity and variety of battery pack designs on the market. Flexible approaches to automated disassembly are required for cost-effective battery recycling.
MTC's Solution
- MTC developed a vision system and task planner to demonstrate machine learning enabled, autonomous automated battery disassembly tasks implemented on an industrial robot controller.
- Whilst the methodology focused on unfastening of bolts, it will be used as a platform for building the other elements required for the autonomous battery disassembly such as cutting into packs, disconnecting cables and pick & place of key components.
The Outcome
- MTC integrated a robot agnostic framework with a server, graphical user interface, Beckhoff PLC, Fanuc manipulator, Atlas Copco spindle, safety systems, and vision system leveraging AI to unfasten bolts.
- Confirmation of correct disassembly bolt object detection techniques and efficient unfastening trajectory generation through shortest path algorithms.
- Design and development of tooling and equipment for disassembly tasks related to unfastening.
Benefits to the Client
- A framework for machine vision driven autonomous robotics has been demonstrated on an industrial robot controller, unlocking autonomous robotics at industrial scale.
- The developed framework is scalable and will underpin future research incorporating other tools and operations to deal with the complexity of existing EV battery packs.
- Work will be continued and transferred to real end-of-life battery packs on a new, bespoke battery assembly/disassembly cell currently being designed by MTC.
The disassembly cell reaffirms MTC’s position as a leader in Electrification R&D. By continuing to work at the cutting edge, MTC will derisk the knowledge required to truly and autonomously disassemble an End of Life battery pack. Leveraging this knowledge onwards with our partner organisations to enable growth.
Marc Henry, Sector Development Manager - Electrification, MTC
