A factory robot now learns to inspect jet engine parts and nuclear components on the fly, adapting to each piece’s unique shape and position rather than following a fixed, pre-programmed path. This matters because safety-critical parts—such as those in aerospace and nuclear systems—often require 100% inspection, yet most of that work is still done manually or by rigid robots. Manual inspection creates bottlenecks that slow production and raise costs, while existing robots cannot handle parts with slight variations in size or alignment. The same problem plagues remanufacturing, where used components are refurbished for reuse. If the project succeeds, factories could inspect and handle parts far faster, cutting costs and improving quality without sacrificing safety. For remanufacturing, this would make it economically viable to reclaim more components, reducing waste and energy use. The research is applied and industry-facing: it combines robot path planning, obstacle avoidance, surface measurement, and non-destructive evaluation into a single automated system. It does not aim to discover fundamental principles, but to solve a concrete production bottleneck that currently limits both manufacturing efficiency and the circular economy.
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High value manufacturing is an essential component of the UK economy, contributing strongly to our economic prosperity and engineering status around the world. The growth in high value manufacturing to support aerospace, nuclear and other high integrity engineering components, has placed huge pressure on the rapid delivery of reliable and high quality Non-Destructive Evaluation (NDE) to inspect these parts. Currently, much inspection of safety critical components (sometimes requiring 100% part inspection) is performed manually, leading to significant bottlenecks associated with the NDE. Existing robots typically follow pre-programmed paths making them unsuitable to handle, inspect and disassemble parts with a significant tolerance or variability. A new end-to-end approach is needed, embracing manufacture, transport through factory, parts alignment, parts tracking, and inspection (both surface form metrology and NDE) with the associated high volume data management feeding into the quality and assurance compliance processes. Exactly the same process bottlenecks occur when we translate the problem to the regime of Remanufacturing, hence the integrated approach taken through this proposal. Remanufacturing has been identified as being central to the creation of economic growth in the UK and global markets. With supplies of resources and energy limited, the transition to a low carbon economy with strong emphasis on resource efficiency is key to the UK's Industrial Strategy. Remanufacturing can support this transition by achieving significant impact in all industrial sectors through preventing waste, improving resource management, generating sustainable economic growth, increasing productivity and enhancing competitiveness. AIMaReM (Autonomous Inspection in Manufacturing& Remanufacturing) provides a unique combination of data collection, processing and visualisation tools combined with efficient robot path planning and obstacle avoidance, with a focus on manufacturing inspection (NDE and surface form metrology). The project will deliver an automated, systems integrated solution, that will be of direct benefit to the manufacturing sector to allow faster integrated inspection and parts handling, thus saving time, and reducing costs whilst enhancing quality and throughput.
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