Michael Elkington
Engineering and Physical Sciences Research Council, University of Bristol
Papers
5
Total Citations
37
H-Index
4
About
Michael Elkington is a leading researcher in the automated manufacture of fibre-reinforced composites, with a focus on bridging the gap between manual craftsmanship and high-speed industrial production. His key research areas include robotic composite layup, defect detection, and human-robot collaboration in manufacturing. Elkington’s major contributions include developing a two-stage automated layup method that combines the flexibility of hand layup with the speed of automation (16 citations), and pioneering the first end effector capable of real-time defect detection during composite layup using tactile shape sensing (10 citations). His work on the Hybrid Vacuum-Robotic (HyVR) process addresses critical defect types like bridging, while his exploration of transportation shells enables rapid, low-cost automotive composite part production. Notably, Elkington has also investigated the human factors of manufacturing, studying laminator trust in human-robot collaboration to improve worker health and productivity. His research is highly impactful for industries seeking to automate composite manufacturing without sacrificing quality, and his innovative sensor-based approaches are paving the way for smarter, safer production environments.
Research Focus
Key Achievements
Top Papers
- 1Automated Layup of Sheet Prepregs on Complex Moulds16 citations · 2016
- 2Real time defect detection during composite layup via Tactile Shape Sensing10 citations · 2021
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- 4
- 5Hybrid vacuum-robotic forming of reinforced composite laminates3 citations · 2022