UK laser systems integrator Cyan Tec has unveiled a fully autonomous robotic sort and segregation system for handling nuclear waste remotely.
The advanced solution, intended for nuclear decommissioning – for which Cyan Tec has previously developed multiple laser cutting systems – will help increase recycling rates and reduce the number of waste containers sent for disposal.
The system assesses the radioactivity and physical characteristics of nuclear waste, and then sorts and segregates it into appropriate containers – using the data collected to inform packaging records.
It does this using a vision system equipped with machine learning. The system acquires 2D images and 3D cloud data of objects to automatically identify individual pieces of waste, which enables them to be handled robotically. The vision system and additional monitoring equipment are then used to autonomously control the robot and gripper selection to segregate and package the nuclear waste.
The new system uses advanced material analysis techniques, including laser-induced breakdown spectroscopy, in order to penetrate the surface coatings of the waste and analyse its base materials.
“Cyan Tec is excited to be pushing the boundaries of AI and robotic technology in the nuclear industry,” remarked Managing Director Tony Jones. “Cyan Tec’s reliable solution is both configurable and scalable, enabling it to handle waste of different sizes and radioactivity levels. Our modular approach means the system can be transferred simply to different nuclear facilities and environments.”
Together with partners Atkins, PSC, the MTC and Applied Photonics, Cyan Tec successfully achieved funding for the development of the new system through the £5.5m ‘Sort and Seg’ innovation competition – launched by Sellafield in partnership with the Nuclear Decommissioning Authority and Magnox. The aim was to reduce waste, reduce manual sorting and increase segregation productivity in nuclear decommissioning.
The key benefits of the new system for the nuclear decommissioning industry include increased sustainability, reduced risks to personnel and significant savings in disposal costs.
