The aviation supplier PFW Aerospace, a subsidiary of the French company Hutchinson, is evaluating the use of Artificial Intelligence (AI) to ensure high non-destructive testing quality standards. An increased economic efficiency in quality assessment is a key benefit of this effort. VisiConsult, the world market leader for customer-specific X-ray systems, has developed a dedicated AI toolbox to automatically evaluate X-ray images. The core of the joint evaluation is the qualification of AI according to demanding aviation test standards.
Convinced by reliability
PFW Aerospace has many years of experience with VisiConsult as a manufacturer of X-ray systems. “Due to the many installed systems, as well as the reliable service, we have been able to experience the great performance of VisiConsult as our X-ray partner,” says Markus Gutensohn, Head of R&D at PFW Aerospace. “When VisiConsult announced that they developed artificial intelligence algorithms to automatically evaluate X-ray image data and they offered a pilot program for this purpose, it was clear to us: We have to join this program. ”
Selected for a unique program
PFW Aerospace was selected as a pilot customer and will receive an AI prototype including test operation and a statistical qualification report. The application is for X-rays of longitudinally welded seams on titanium tubes. The test parts are subject to very high-quality standards because they are installed in aircrafts around the world. PFW will collect X-ray images over a defined period of time, which VisiConsult will then use as a basis to train AI networks. The Ai itself is operating on secure industrial platform developed in collaboration with the AI pioneer FUJITSU.
Qualification by testing
In order to qualify this new technology according to the demanding inspection standards, sufficient statistical data about the accuracy of the algorithms must be available. Therefore, there is a permanent comparison of the AI results with the decisions of experienced NDT inspectors. With the help of this input, the neuronal networks are also regularly re-trained. Only when a sufficiently good detection probability (POD) has been proven the system can be qualified and used in production.
More quality through more intelligence
PFW Aerospace sees artificial intelligence for defect interpretation as a future-oriented tool for its quality department: “This will save our employees a lot of time interpreting X-ray images, and this time is ultimately available for other important tasks.” The use of AI is expected to significantly increase the efficiency of non-destructive testing. It sorts out components with detected deviations and only forwards the necessary X-ray scans to the inspectors for final approval by humans. The information about defect locations and trends can also be sent to the development team in order to optimize design data. Gutensohn assures: “The final quality approval will continue to be done by our highly qualified NDT colleagues.” The motto here is: Safety First!
Figure 1: Mr. Gutensohn of PFW
Digital revolution as the igniter for AI
For Lennart Schulenburg, Managing Director at VisiConsult, the fact that Artificial Intelligence is the next step in quality assurance is a logical consequence of the digital revolution: “Our inspection systems generate a magnitude of digital images and data that has to be evaluated and transformed into information. This amount of data is hardly manageable for humans, but it can be processed with high precision by AI systems. Therefore, we see AI as a helpful tool to assist humans to perform more effectively at their job. This can be best compared to a lane-keeping assistance feature in a car that.”
Further pilot projects from other industries
VisiConsult is planning further pilot programs, also from other industries such as oil & gas and automotive. Companies that are interested in the program and would like to apply can find all the information at www.visiconsult.de/smart-inspection – there interested companies can apply for the waiting list of the pilot program or request a free initial analysis.
Related videos:
By loading the video, you accept YouTube's privacy policy.
More information
Jason Robbins about why AI will be essential in the near future of NDT?
Machine learning as a supply for automatic defect recognition is important to the NDT sector because it is a data driven trend and the NDT sector supplies a lot of the data. To recreate the data it is our job to help the company to use it and to improve processes…