SIMPL (Space, Information, Mobility, Power and machine Learning)

Aerospace factories currently spend 80% of their build time on sub-assembly work done entirely by hand, and this project aims to replace that manual labour with fleets of robots. The problem is straightforward: skilled workers are scarce, and without automation, manufacturers cannot ramp up production to meet demand. The SIMPL project tackles five specific barriers to robot adoption in aero-structure manufacturing. It will develop digital twins that let robots be programmed and qualified off-line, create affordable simulation tools for the supply chain, use sensor-equipped autonomous mobile robots to move process robots around the factory floor, minimise energy consumption, and apply machine learning to existing drill sensors to improve quality control and predict fastener lengths. If successful, the project will push these automation technologies to Technology Readiness Level 6—meaning a fully functional prototype demonstrated in a relevant environment. The immediate impact is on manufacturing efficiency: faster production, lower costs, and reduced reliance on scarce skilled labour. The broader effect is on supply chains, where smaller suppliers could adopt affordable simulation tools to integrate their own automation. This is applied engineering, not fundamental science; the goal is a practical, deployable system for a specific industrial bottleneck.