DESCRIPTION
There has been a lot of “buzz” around artificial intelligence (AI) and machine learning (ML) in the field of nondestructive testing. This roundtable discussion will give the audience a good understanding of what AI/ML is as applicable to NDT and where we are today with this emerging field. The discussion will highlight how a collaborative effort with experts in the field along with the core NDT community can bring in a revolution to make this technology successful for NDT applications. The highlights of ASNT’s effort to make this possible will also be presented in this session.
CONTRIBUTORS
- Dr. John C. Aldrin obtained his Ph.D. degree in theoretical and applied mechanics from Northwestern University in 2001, and master’s and bachelor’s degrees in mechanical engineering from Purdue University in 1996 and 1994, respectively. Since 2001, he has been working as the principal of Computational Tools, specializing in NDE modeling and simulation, data analysis, inverse methods, and reliability assessment. Dr. Aldrin has worked in a Visiting Scientist position with the Air Force Research Laboratory leading research on computational methods in NDE, led assisted data analysis (ADA) software development tools for NDT applications with SAIC and TRI/Austin, and participated in the NASA Engineering and Safety Center Nondestructive Evaluation Technical Discipline Team. Dr. Aldrin has co-authored over 170 journal articles, conference presentations, and book publications in the field of nondestructive testing and is a Fellow of ASNT.
- Raj Venkatachalam has been involved in the field of nondestructive evaluation (NDE) for 18+ years and is currently the Systems Engineering Manager at VMI – A Varex Imaging Company. Raj has a master’s degree in electrical and computer engineering from the University of Waterloo and a bachelor’s in electronics and communication engineering from the University of Madras. He has several certifications in systems and reliability engineering. He is an active member of ASNT and has contributed significantly to the ASTM standards for digital radiography (DR). At VMI, Raj is working on developing engineered solutions using robotics and analytical tools to enable next generation tools for radiography.
Raj is considered as a subject matter expert (SME) in the field of digital radiography and has close to 10 patents to his credit. Raj was one of the pioneers to successfully develop a flat-panel-based subsea detector that was demonstrated successfully to work under water up to a depth of 10 000 ft (3048 m). Raj has participated in several inspection-related challenges and his solution for inspection of grouting on offshore wind turbines was declared as the winner in the Carbon Trust Offshore Wind Accelerator (OWA) competition. He also participated in the Technology Challenge conducted by Petrobras in Brazil and his idea of developing a flat-panel-based CT system for inspection of structures underwater was selected. He has a patent filed on this and the product is being developed now for deployment.
Raj is also the Chair of ASNT’s Artificial Intelligence/ Machine Learning (AI/ML) Committee where he is collaborating with industrial and academic experts in this field to develop guidelines for AI as applicable to the NDT industry. - Suhaib Zafar holds two graduate degrees in mechanical engineering, focusing on computational modeling of systems involving heat transfer, chemical kinetics, and fluid flow. His undergraduate degree was in aerospace engineering, with a research focus on nondestructive testing and structural health monitoring (NDT/SHM). A major component of his graduate work was applying machine learning to engineering problems, with a focus on complementing computational methods with data-based techniques. At present, Suhaib is an NDT Research Associate for TechKnowServ Corporation, with a particular focus on acoustic emission (AE) testing. His prime responsibilities are data analysis and reporting, updating procedures for testing, supervision, teaching , and research. He has been a member of ASNT since August 2021 and serves a member of the AE Committee under the Methods Division, the TT Committee, the AI/ML Committee, the Mentoring Committee, and the Research Council (RC). He is also a member of the E.07 Committee (NDT) of ASTM and the ASME Thermal Energy Storage (TES) Committee Interest Review Group (IRG), by invitation.