Short Course B: AI in Digital Radiography: Practical Implementation, Validation, and Workflow Integration
Instructor-Led Training
Learn how AI-assisted defect recognition can improve Digital Radiography accuracy, speed, and reliability. This practical short course helps NDT technicians, Level III supervisors, and managers evaluate suitable use cases, implementation requirements, validation needs, and workflow integration for real-world inspection environments.
Credit Info
- Contact Hours: 4
- IACET CEUs: N/A
- Valid for ASNT Level III recertification: Yes
- Renewal Category: B
Course Overview
This short course introduces the practical use of artificial intelligence in industrial Digital Radiography, with a focus on AI-assisted Automated Defect Recognition and its role in improving inspection accuracy, speed, and reliability. The course is designed for NDT technicians, Level III supervisors, and managers who are responsible for radiographic inspection performance, workflow efficiency, technical oversight, and investment decisions.
Participants will learn what AI can realistically contribute to Digital Radiography today, where its limitations remain, and how it can be implemented without weakening the role of qualified NDT personnel. The course will explain the difference between manual image interpretation, rule-based automation, and modern AI-assisted defect recognition. It will also address key implementation topics, including training data, image quality, validation, workflow integration, human review, and acceptance responsibility.
A central theme of the course is the use of AI as a second layer of scrutiny. Attendees will examine how AI can reduce interpretation variance, support inspectors during repetitive image review, help identify indications that may otherwise be missed, and reduce bottlenecks in high-volume inspection environments. Practical examples from industrial radiography will be used to discuss common benefits, such as faster image triage, improved consistency, better use of scarce expert time, and reduced rework caused by false calls or delayed defect detection.
The course will also provide a practical decision framework for organizations considering AI implementation. Participants will compare in-house development with the use of specialized solution providers, including considerations such as dataset availability, model validation, software integration, support, scalability, and total cost of ownership.
By the end of the course, attendees will be able to identify suitable AI use cases in Digital Radiography, recognize the main technical and organizational requirements for implementation, ask the right validation questions, and apply a structured approach for introducing AI into existing NDT workflows.
Upon Completion, Learners Will Be Able To:
- Identify suitable AI-assisted defect recognition use cases within existing Digital Radiography workflows.
- Evaluate key implementation requirements, including data quality, validation, workflow integration, and human review.
- Compare in-house AI development with solution-provider approaches using practical criteria such as cost, scalability, support, and inspection reliability.
Meet the Instructor
Lennart Schulenburg
Lennart Schulenburg is an NDT expert and Managing Director at VisiConsult X-ray Systems & Solutions. With a background in computational informatics and an MBA from one of Germany’s top business schools, he leads cutting-edge research in digital radiography and automation. A frequent speaker at global industry events, Lennart shares insights on emerging NDT technologies and Industry 4.0. His forward-thinking approach reflects his motto: “It’s never a problem, rather a challenge.”
Questions? Contact us at education@asnt.org