A-STAR: Aerospace Standardisation Technology for Assembly and Repair

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.