HEUFT is showcasing its deep-learning AI inspection lineup at interpack 2026, using camera and X-ray processing technologies alongside new IT solutions to identify tiny contaminants in packaged food.
HEUFT’s reflexx X-ray image processing uses deep learning, proven image analysis, and a multi-layered neural network to identify tiny contaminants – e.g., glass splinters and metal fragments – in glass food jars.
It is suitable for non-homogenous product masses with cavities of varying sizes between their individual components, as well as irregulat structures that absorb X-ray pulses to varying degrees.
Believed to exceed the capabilities of conventional X-ray technologies, reflexx is expected to detect dangerous bodies in real time and distinguish them from harmless product and packaging components.
This approach is hoped to eliminate false rejections during the inspection process and avoid unnecessary food and packaging waste.
The HEUFT reflexx AI camera can reportedly evaluate and verify product markings, even when they are distorted, smudged, or blurred. It can identify incorrect or absent best-before dates, closures in the incorrect position, sealing foil that protrudes beyond the lid, cap colours that do not match the product, and more.
Unsuitable packaging is removed from the production line using sorting systems like HEUFT’s DELTA-FW flow rejector – reducing the risk of incorrectly labelled composite packaging with leaking or prematurely spoiled contents reaching the retail market.
Meanwhile, the HEUFT eXaminer XS uses deep-learning AI in pulsed X-ray inspection to inspect filled food jars with full coverage, sensitivity, and assessment power – especially during glass-in-glass detection processes.
This slim turnkey solution is designed to achieve full detection reliability when inspecting tins, doy packs, squeeze bottles, stand-up pouches, and cartons. It denoises X-ray images and removes artefacts to identify small contaminants, including hard plastic fragments and metal particles.
The modular system can be equipped with one or two sidewall X-ray flashes to cover the entire fill volume. When combined with the HEUFT reflexx, it is believed to increase the precision of foreign body detection; this combination is also thought to unlock an ‘unfolded’ view to detect particularly small foreign objects lying flat on the base of carton packs containing a liquid.
When using a single detection unit, an optional angled orientation is set to help operators cover the entire volume of tall filled containers. A full-field image converter has been implemented to identify foreign bodies anywhere in the packaging.
The examiner’s highly automated HEUFT SPECTRUM control unit can be linked to various detection functions, including precise verification of product marking and automatic adjustment of the upper X-ray flash module’s height and alignment. The HEUFT NaVi user guidance also offers audio-visual step-by-step assistance for operators.
Other solutions on show include HEUFT’s Multi Colour Image Processing, said to cover the complete finish areas of wide-mouth jars and reveal fine cracks on the sealing surface; lateral laser profile measurement, designed to spot small leaks in filled cardboard composite packaging during the integrity testing process; and state-of-the-art IT solutions encompassing production data acquisition, line analysis, brand and recipe management, and end-to-end track-and-trace.
Visitors at interpack can view HEUFT’s full lineup at Stand A45 in Hall 13.
At the same event, Körber is showcasing its fully automatic inspection machine for High Mix Low Volume (HMLV) applications. This product is anticipated to unlock reliable inspection for small batches with frequent product and format changes – e.g., syringes, vials and cartridges – without compromising quality or efficiency.
In other news, Mettler-Toledo Product Inspection has announced its X56 DXD+ dual energy photon-counting X-ray system with AI capabilities. This solution is designed to help manufacturers inspect their packaged goods with enhanced contamination detection capabilities.
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