The manufacture and safe operation of engineering assets ranging from aircraft to power stations is predicated on sophisticated Non-Destructive Evaluation (NDE) using inspection techniques such as ultrasound, eddy-currents and x-rays. Currently, the majority of NDE data is irreversibly condensed after an inspection is performed, sometimes to as little as a binary pass/fail classification. In doing so, a wealth of useful information that could impact on the future safety and economic utility of an asset is lost forever. However, as the fourth industrial revolution unfolds, the enabling infrastructure to store raw NDE data from every inspection is becoming available. Storing raw NDE data is itself important, as it future-proofs individual measurements against new processing techniques as they become available. However, from a data science perspective it also provides an opportunity to extract much more information about the integrity of an engineering asset by considering multi-modal NDE data collectively over the lifetime of the asset and in the context of data streams from other condition-monitoring modalities.

This workshop will gather experts from industry and academia to discuss the opportunities and challenges for applying data science techniques to NDE.

SCHEDULE:

10.00 – 10.15 Registration. Coffee and tea at arrival
10.16 – 10.45 Welcome and Introduction, Prof Paul Wilcox (University of Bristol)
10.45 – 11.10 Machine learning methods for condition monitoring, Prof Ian Nabney (University of Bristol)
11.10 – 11.30 Coffee break
11.30 – 11.55 Data Centric Engineering: Hype, Hoax, or Hope?, Prof Mark Girolami (Turing Institute)
11.55 – 12.20 Data Science Use Cases and Examples - Richard Jarvis (Emis Group Plc)
12.30 – 13.30 Lunch
13.30 – 13.55 Data Science Opportunities for the Manufacture and Inspection of Naval Assets, Dr Tom Barber (BAE Systems)
13.55 – 14.20 Opportunities for NDE in digital twins of engineering infrastructure, Prof Eann Patterson (University of Liverpool)
14.20 – 14.45 Coffee Break
14.45 – 15.10 The application of digital assets for flexible maintenance of industrial gas turbines, Jon Douglas (Frazer-Nash Consultancy)
15.10 – 15.35 Machine Learning for Ultrasonic Fault Detection. Niels Jeppesen (DTU)
15.35 – 16.00 Wrap up and close