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Non-Destructive Evaluation (NDE) Data Science for Industry 4.0

May 22 -10:00 am - 4:00 pm

Free
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The Ultrasonics and Non-Destructive Testing Research Group at the University of Bristol is holding a one day workshop to gather experts from industry and academia to discuss the opportunities and challenges for applying data science techniques to NDE.

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.

Registration

Registration is free via Eventbrite.

https://www.eventbrite.co.uk/e/non-destructive-evaluation-nde-data-science-for-industry-40-tickets-59956294892

Workshop Agenda

10.00 – 10.15 Registration. Coffee and tea at arrival

10.15 – 10.45 Welcome and Introduction, Prof Paul Wilcox (University of Bristol)

10.45 – 11.10 tbc – Mark Girolami (Turing Institute)

11.10 – 11.30 Coffee break

11.30 – 11.55 tbc - Richard Jarvis (Emis Group Plc.)

11.55 – 12.20 Data Science Opportunities for the Manufacture and Inspection of Naval Assets, Dr Tom Barber (BAE Systems)

12.30– 13.30 Lunch

13.30 – 13.55 Machine learning methods for condition monitoring, Prof Ian Nabney (University of Bristol)

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 Tbc

15.10 – 15. 35 Tbc

15.35 – 16.00 Wrap up and close

Organiser

University of Bristol
Website:
www.bristol.ac.uk

Venue

Mercure Bristol
Broad Street
Bristol, BS1 2EL United Kingdom
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NRC