The Bullfrog project pioneers a long-awaited step transformation for composites manufacturing Non-Destructive Testing (NDT); a fully automated, low-cost, non-contact in-process NDT solution that seamlessly integrates into manufacturing lines in a non-intrusive manner at critical junctures early in the composites manufacturing process. By identifying defects as early as even the layup stage, Bullfrog is poised to significantly improve composite manufacturing yield rates and rewrite industry standards, reducing product and environmental waste by up to 40% or more -- a huge leap forward for UK Net Zero initiatives and ATI's Destination Zero program. It is designed with aerospace industry needs in mind and seeks to provide a holistic solution to aerospace composite manufacturers of today. The core innovation of Bullfrog lies in its unique sequencing and optimisation of multiple state-of-the-art Active Thermography (AT) signal-processing techniques to enable low-cost Uncooled Infrared (IR) Cameras to provide Signal-to-Noise Ratios (SNR) near equivalent to Cooled IR Cameras at a fraction of the price - with none of the traditional drawbacks involved in cooling - thereby unlocking the full potential of Uncooled IR Cameras for composite NDT. Preliminary research and initial testing of the technology have already shown promising results in defect detection for aerospace-grade CFRP panels, with subsurface defect identification accuracy of over 90%, which the project looks to further refine. These Uncooled IR Cameras are rigged on portable, lightweight cobot (collaborative robot) arms with portable excitation sources. The cobot integrates machine vision to facilitate a fully automated scanning process - this combined with a deep learning AI classifier for automatic categorisation makes Bullfrog an independent modular solution that can truly scale to sector despite industry deficits of NDT experts. The entire scanning and analysis process is projected to take less than 2 minutes. Bullfrog's contribution to high-rate composite manufacturing is projected to make waves in solving supply chain shortages across the Aerospace industry and drive down costs, supporting efficiency-driven aircraft conversions, retrofits, and Aerospace R&D. This impact potentially extends far beyond Aerospace -- the Automotive, Defence, Medical, Electronics sectors and more will similarly enjoy the effects of higher yield, lower waste composite manufacture -- with the UK as its debut stage, then the world. The Bullfrog project is a collaboration between Easol, Brookhouse Aerospace, University of Southampton, Cranfield University, and Createc, and has support from major aerospace primes (Boeing, BAE), the National Composites Centre (NCC), other composite manufacturers (GTR).

Within our A-STAR\* (Aerospace Standardisation Technology for Assembly and Repair) project we aim to deliver productivity, material and energy efficiency improvements in aerospace manufacturing by focusing on the development and demonstration of VIOLET: an innovative Artificial Intelligence (AI) assembly assistant based on advanced computer vision, capable of automatically checking digital manufacture route-cards: * automatic defect detection thereby reducing the in-process assembly errors * traceability & compliance via automatically generated historical records * automatic skill capture on the factory floor for operator training and knowledge dissemination The project will start with a focus on material and energy-intensive aerospace assembly processes with Dunlop Aircraft Tyres as the lead demonstrator - the UK's largest Aerospace Tyre Manufacturer - and then demonstrate aerospace scalability through deployment and testing at Brookhouse Aerospace, a leading manufacturer of composite structures for civil and defence. A-STAR will leverage state-of-the-art AI computer vision to recognise operator actions on assembly processes to ensure that stringent aerospace quality standards are met. The use of convolutional neural networks offers more generalisability for pattern recognition and performs better for detecting anomalies compared to traditional automated optical inspection. A digital record of the actions that have been performed on a product can then be stored as a proof of quality management as well as be used to train new special-process operators. This record is useful for digitally connecting factories so that defects can be traced through supply-chains and used to prove quality standards. We are innovating beyond state-of-the-art computer vision and human action recognition, bringing AI to human action data in aerospace manual processes and in the long-term advancing the way in which people work in manufacturing. When delivered, A-STAR will become the template for AI-assisted assembly, delivering energy and material reduction and enable a sustainable, energy-resilient approach to assembly and repair operations.

A supply chain grouping working under the North West Aerospace Alliance's Aerospace Supply Chain Excellence programme has identified the commercialisation and industrialisation of 3D textile technology as a key priority for the advanced composite sector in the UK. INTERTEX is an Research and Development Project, supported by the Technology Strategy Board (TSB), that aims to provide a step change in the competitiveness of the UK composites industry to produce high performance, high added value, hollow structural parts such as engine nacelles, UAV fuselages with tech transfer opportunities to other sectors such as wind turbine blades and bus/train carriages. The project consortium is being led by the NWAA, and includes industry partners Aircelle, Sigmatex, Kaman Composites, Hyde Group and Trelleborg Offshore UK, and the Academia Partner North West Composites Centre (through the University of Manchester).