Heuft will present innovative technologies for error detection at interpack 2026. With deep learning methods, X-ray and camera images will be analysed more efficiently to increase product safety.
In the packaging industry, the precise detection of faults and foreign objects is gaining increasing importance. Heuft will be presenting its latest developments at interpack 2026, which are based on deep learning technologies. These technologies enable a more in-depth analysis of X-ray and camera images, leading to improved consumer and brand protection.
New possibilities for X-ray image processing
The Heuft reflexx A.I. X-ray image processing is capable of detecting even invisible foreign objects in structured, inhomogeneous products such as pickled gherkins. This technology intelligently distinguishes between critical and non-critical objects, thus significantly improving quality assurance.
Efficient inspection of food jars
The Heuft eXaminer II XAC offers high sensitivity and discernment in the pulsed X-ray inspection of filled food jars. Particularly in glass-in-glass detection, complete coverage is ensured, which increases detection reliability.
Compact solutions for foreign object detection
The Heuft eXaminer II XS, a compact solution for foreign object detection in cans, impresses with its reduced false rejection rate. This solution uses pulsed X-rays and Heuft reflexx A.I. to ensure the highest detection reliability.
Intelligent camera for product marking
Another innovation is the Heuft reflexx A.I. camera, which, in combination with deep learning-capable image processing, reliably verifies product labels, such as best-before dates, even in the event of tampering.
Comprehensive IT Solutions
In addition, Heuft offers IT solutions ranging from production data acquisition and line analysis, through product and recipe management, to end-to-end track & trace. These solutions ensure efficiency, transparency, and traceability in the filling and packaging process.
Heuft at interpack 2026: Hall 13, Stand A45
Source: Heuft
