| Developers: | Innopolis University |
| Date of the premiere of the system: | December 2025 |
| Branches: | Electrical and Microelectronics |
| Technology: | Computed tomographs |
2025: Product Announcement
In December 2025, Innopolis University introduced an industrial robotic ultrasound tomography (SPRUT) system created to control the quality of metal products. The system was developed by specialists from the Center for the Development of Industrial Robotics of the IT University.
According to the press service of Innopolis University, the SPRUT complex is designed to automatically identify internal defects in complex metal parts. The system is a robotic manipulator with an integrated ultrasonic flaw detector - an instrument that sends sound waves to detect hidden cracks, voids and weld violations. The object under study is placed in a 100-liter working bath.
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According to the developers, SPRUT detects internal defects 30% more efficiently and increases the sensitivity of control by 20% compared to traditional manual methods. The solution is addressed to metallurgy, aircraft and railway engineering, as well as electronics manufacturers.
The key feature of the complex is the complete robotization of the process. The manipulator accurately positions the ultrasonic sensor relative to the surface of the part. The system includes the function of saving and loading measurement results, which creates a digital cycle of quality control in production. The software allows you to control the equipment, calibrate the part, build a scanning path and visualize data in 3D model format with the ability to view slices.
Renat Adutov, technical director of the Center for the Development of Industrial Robotics at Innopolis University, said that work on the project has been carried out since 2024. According to him, SPRUT displays the control results "in the form of three-dimensional visualization and its flat slices along different axes" in contrast to analogues that provide only two-dimensional images. "Such a system will allow you to get the most complete information about the quality of the product - from a general 3D map to the microstructure of a specific defect," Adutov explained.[1]
Notes
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