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Role of Machine Learning and AI in NDT

Webinars 07 May 2024

Webinar on the Role of Machine Learning and AI in NDT

TIME: 11am-1pm, BST, UK

This webinar will give an overview of the role of Machine Learning and Artificial Intelligence in Non-Destructive Testing.

The following topics will be presented during this 2 hour FREE webinar.

  • An overview of robotic inspection
  • An introduction to machine learning and AI in NDT data analysis and use in defect detection 
  • Machine learning and AI in NDT for path planning and automation
  • Inspection data visualisation, big data digital twins and advances post-processing 
  • Eddy Current Array Testing in lieu of Magnetic Particle Inspection and Fluorescent Penetrant Inspection  
  • Training and competence management in today’s NDT industry

At the end of the presentations there will be time for a question and answer session and discussion about the topics raised in the webinar. 

Meet the team

Dr Kai Yang - Senior Project Leader, NDE/Inspection and Site Services

Dr Kai Yang

Senior Project Leader, NDE/Inspection and Site Services

Dr Kai Yang is a Senior Project Leader, in the NDE/Inspection and Site Services section for technology at TWI. Kai is now a specialist in artificial intelligence (AI), long-range ultrasonic testing, signal processing, and structural health monitoring. He is leading the AI theme map for the NDE group.

Mengyuan Zhang - PhD Student

Mengyuan Zhang

PhD Student

Mengyuan Zhang, a PhD student at BRUNEL University specializing in Mechatronics and Robotics, has been actively involved in innovative projects conducted in collaboration between TWI and BRUNEL University since joining. These projects aim to address the quality and safety challenges brought about by the rapid growth of modern industries, seeking cost-effective solutions. Her research focuses on leveraging robotic automation technology to enhance the efficiency and cost-effectiveness of Non-Destructive Testing (NDT). By integrating technologies such as the HUSKY mobile platform, robotic arms, and depth cameras, she is dedicated to developing an automated NDT solution that is both efficient and economical.

Nathan Hartley - Team Manager, Robotics

Nathan Hartley

Team Manager, Robotics

Nathan Hartley is an experienced Chartered Engineer and Project Manager with more than 20 years’ experience in the defence, nuclear, energy, manufacturing and non-destructive testing industries. Since joining TWI in 2018 he has managed a variety of complex and high value engineering and research projects with a focus on automation and development of novel NDT techniques. He recently introduced multi-frequency microwave inspection to TWI’s capabilities and has been instrumental in the integration and use of mobile and collaborative robots. He has also overseen the development of a novel, automated acoustic inspection method for the inspection of highly attenuative glass fibre structures. Nathan is also an accomplished NDT practitioner, holding CSWIP Level II qualifications in UT and PAUT (Welds).

Owen Rees-Lloyd - Senior Project Engineer

Owen Rees-Lloyd

Senior Project Engineer

Owen Rees-Lloyd is a senior project engineer at TWI with more than 5 years industrial experience in non-destructive testing (NDT).  Having joined TWI in 2016, Owen spent his first 3 years at TWI as a PhD student working on Electromagnetic Acoustic Transducers. Following his PhD, Owen joined TWI as a project engineer, leading and delivering a wide range of engineering and research projects within NDT. More recently, Owen has been working on robotic deployment of NDT inspections, with a particular focus on eddy current technologies, along with development of coded excitation ultrasonic systems, and the application of Total Focussing Method (TFM) technologies.

Mark Sutcliffe - Consultant, Software

Mark Sutcliffe

Consultant, Software

Consultant (software), responsible for the design, implementation and delivery of ultrasonic data acquisition and imaging software solutions. Algorithm development, Full Matrix Capture (FMC), machine learning and Virtual Source Aperture (VSA).

For more information please email: