Make plans to join us for a summit on the future of Nondestructive Testing (NDT) as artificial intelligence and machine learning become more prevalent in our society. The summit aims to bring together professionals, researchers, and enthusiasts from various sectors to discuss the latest trends, innovations, and challenges in AI/ML in NDT.
This event is FREE to ASNT members! $99 for non-members.
Date: 21 September 2023
Time: 11:00 a.m. - 2:00 p.m. (ET)
Where: Online
NDT has long been the cornerstone of quality assurance and safety in aerospace, manufacturing, oil & gas, energy and power generation, rail transportation, and beyond. It involves various techniques that allow us to assess the internal properties of materials and structures without causing damage. In the era of rapid technological advancement, we find ourselves at a pivotal juncture where AI and ML hold the potential to amplify the capabilities of NDT to unparalleled heights.
The fusion of AI and ML with NDT brings a paradigm shift. By leveraging the power of data-driven insights, predictive analytics, and pattern recognition, we can enhance defect detection accuracy, optimize maintenance strategies, and propel industries into a new era of efficiency and reliability. But, as with any transformative technology, this journey comes with challenges – from data acquisition and preprocessing to interpretability and ethical considerations.
Convergence is not just a gathering of minds; it is a pivotal moment in the evolution of emerging technology. It represents our dedication to pushing the envelope, embracing change, and ensuring our industries remain at the forefront of progress. Together, we embark on a journey that has the potential to redefine how we understand and harness the capabilities of materials and structures. This summit aims to tackle these challenges head-on, fostering discussions and collaborations that will shape the future of AI/ML in NDT.
The time zone below can be adjusted if necessary.
Speakers
Evan Acharya
The Why and How of AI Co-Pilots
Evan Acharya is an expert in applying Deep Learning to enterprise use cases. He has leveraged Deep Learning to execute projects in diverse fields such as defect detection, disease identification, and chemical synthesis. He has co-founded multiple AI startups in the computer vision and natural language domains. He has worked as a Software Engineer at Motorola, Strategy Consultant at Booz & Company, and Solutions Architect at NVIDIA. He holds a Master of Computer Science from the University of Illinois Urbana-Champaign and an Master of Business Administration from the University of Chicago.
Debejyo Chakraborty
Process Monitoring for Quality Evaluation
Dr. Debejyo Chakraborty has been with General Motors (GM) Global Research and Development for over twelve years. As a Staff Researcher in the Manufacturing Systems Research, he develops AI algorithms for process monitoring and non-destructive quality prediction. His research contributed to bringing the Chevy Volt advanced battery to production. His current focus is in Li-ion cell quality prediction. He has received the Boss Kettering award, highest recognition for technical innovation at GM. Debejyo has also been a recipient of Outstanding Young Manufacturing Engineer by SME. His contributions are published as technical publications and patents. Debejyo has a PhD in Electrical Engineering with a specialization in Digital Signal Processing from Arizona State University. He is a Senior Member at IEEE, and is the current Vice President and Treasurer of Sigma Xi GM Chapter.
Patrick Howard
Standardization for Digital Inspection and Data Analytics
Patrick Howard has been involved with standards development for digital inspection data through ASTM International since 2004. He was as the subcommittee chair for ASTM E07.11 on Digital Imaging and Communication in NDE (DICONDE) from 2006-2018. During that time, the subcommittee issued seven new standards, expanding DICONDE to cover multiple NDT modalities. He recently served as the task group leader for developing the ASTM E3327-21 Standard Guide for the Qualification and Control of the Assisted Defect Recognition of Digital Radiographic Test Data, which discusses best practices when deploying AssistDR systems in manufacturing environments. He is currently chairing the E07.99 subcommittee on Liaison, improving E07’s connections to other standard development organizations. Patrick holds a Bachelor of Science in Electrical Engineering from Michigan Tech and a Master of Science in Electrical Engineering from the University of Minnesota. He is currently a Consulting Engineer for NDT at GE Aerospace.
Cara Leckey, PhD
Opportunities for AI/ML tools for Aerospace
Cara Leckey, PhD, joined NASA in 2010 as a Research Physicist in the Nondestructive Evaluation Sciences Branch (NESB), where she spent many years leading research in computational nondestructive evaluation focusing on ultrasound modeling. Since joining NASA, she has also served as project lead of the NASA Langley High-Performance Computing Incubator (HPCI) project, the Assistant Branch Head and Branch Head of the NESB. She currently serves on a temporary detail as the Center Transformation Portfolio Manager for NASA Langley.
Harry E. Martz, Jr., PhD
Methods to Nondestructive Characterize AM Parts
Harry E. Martz, PhD, is the Director of the Nondestructive Characterization Institute and a distinguished member of the technical staff at Lawrence Livermore National Laboratory. Harry is leading a team of scientists and engineers to research, develop, and apply nonintrusive characterization methods to better understand material properties and inspection of components and assemblies.
Vincent C. Paquit, PhD
Augmenting NDE/NDT using Digital Twin Technology and AI
Dr. Vincent Paquit holds the position of Section Head for Secure & Digital Manufacturing in the Manufacturing Science Division, and he also serves as the Data Analytics lead for the Manufacturing Demonstration Facility (MDF), both roles being based at the Oak Ridge National Laboratory. Within the MDF, he leads a team of scientists and engineers dedicated to developing a Data Analytics Framework for Advanced Manufacturing. This framework generates digital twins of manufactured components and extensively leverages AI for information extraction. The primary goal of this framework is to enhance the comprehension of manufacturing processes, facilitating part certification and qualification, as well as supporting the implementation of process-informed design, inspection, control, and correction.
Lennart Schulenburg
AI in RT – Learnings from Several Implementations
Lennart Schulenburg is an author and expert in Nondestructive Testing and quality control. As CEO of the X-Ray innovator VisiConsult X-ray Systems & Solutions from Northern Germany, he has extensive experience in industries ranging from automotive to aerospace.
Walter Weber
Improving Machine Learning Results by Automating Input Data Classification and Labelling
Walter Weber is CEO of UTEX Scientific Instruments. Since 1992 he has led a group of programmers, scientists and engineers that live to solve nondestructive inspection problems. Walter encourages new ways of thinking about how to automate NDT, and believes there is much work to be done to ensure that NDT catches up with the rest of factory automation. UTEX produces inspection automation software, ultrasonic instrumentation and mechanical scanning systems for the aerospace, nuclear and power generation industries.
Moderators
Anish Poudel, PhD
Anish Poudel, PhD, is the Principal Investigator II - NDE within the R&D department of MxV Rail, a wholly-owned subsidiary of the Association of American Railroads. Poudel earned a Bachelor of Science from the University of Evansville and Master of Science and a PhD from Southern Illinois University in Mechanical Engineering focusing on NDE. At MxV Rail, Poudel currently provides technical leadership and manages various inspection and detection research projects. Poudel has served on the ASNT Board of Directors, was a past chair of the ASNT Research Council, and is currently chair of the Engineering Council AI/ML Committee.
Raj Venkatachalam
Raj Venkatachalam has diverse work experience spanning several companies. Raj currently holds the position of Senior Systems Engineering Manager at Varex Imaging Corporation. Raj is chair of ASNT’s Artificial Intelligence/ Machine Learning and serves on the ASNT India Board of Directors.