How is artificial intelligence (AI) being implemented for quality control exactly and what potential does it offer food manufacturers?
ProSweets Cologne exhibitors will provide answers to these questions at the trade fair from 2 to 5 February 2025*.
AI applications for monitoring the production in the sweets and snacks industry go far beyond simple chatbots, indeed they use advanced technologies to improve a host of processes.
An innovative implementation of AI in the food industry that will be presented at the Cologne fairgrounds is improving quality control using machine vision. The machines on display in Hall 10.1 are equipped with smart cameras and AI-based tools that observe, learn and adapt. The systems enable total transparency of the production processes in real-time.
Process transparency in real-time
“The potential of AI and machine learning is huge and will fundamentally change the processes of the companies – also in the field of quality assurance,” emphasised Guido Hentschke, Director of ProSweets Cologne.
Instead of “just” recording data, AI can analyse trends and predict future results. By using advanced algorithms it reveals hidden inefficiencies and delivers recommendations of action to increase “the reliability and flexibility of the production and optimise the use of resources,” Hentschke stated.
Automated inspection systems are one of the most important AI applications in the sweets and snacks industry. Thanks to the implementation of computer vision and algorithms of machine learning, modern solutions like the ones also on display in Cologne offer an unprecedented level of precision – for example in recognising defects in biscuits, wafers and crackers. Whether round or square, sweet or savoury, made of wheat or oats: Even slight deviations on complex surfaces are detected on the conveyor belt directly after leaving the continuous oven – this minimises production stoppages and waste and goes hand in hand with the producers’ commitment towards more sustainability.
Visual quality control intelligently optimised
The special feature is that AI assesses the products individually and allocates quality indicators. Holes, breakages, insufficient coating and oozing chocolate are labelled as rejects. Deficits like bubble entrapments or smaller scratches are also detected, but here there are higher tolerances. The quality controls not only have to recognise cracks or colour defects. Foreign bodies have to be detected immediately, before the bakery products reach the trays.

Users can thus carry out complex sorting and quality controls for irregularly formed items, which is difficult, if at all possible, to carry out using rule-based vision systems. In contrast to humans, AI systems are able to scan hundreds of products a minute continually and find tiny flaws or contaminations, which could impair the quality of the food. AI especially demonstrates its advantages in highly-automated packaging lines where the priority lies on speed, flexibility and efficiency. This ensures that only goods that meet the strict quality demands reach the consumers.
An eye on everything during the snack check
In addition to the established R(ed)-G(reen)-B(lue) camera technology and the laser scan, more and more systems that work in the ultraviolet or infrared wavelength range have recently been implemented to inspect food. The reason for this are tasks that can no longer be solely solved using sensors that work in the visible wavelength range. Here, the hyperspectral image processing reaches down to molecule level. It allows the chemical composition of the products to be assessed spatially-resolved inline and in real-time. And even if test objects with a higher variance have to be inspected and sorted, like dried fruits and nuts, AI is no longer a future vision. With the aid of Deep Learning, modern vision systems decide whether an object belongs in a snack mix or whether it is a foreign body. All foreign bodies, whether plastic, stones, metal or fragments of glass are removed in just one step. It is also possible to determine the bitterness of almonds and have them discharged safely, where necessary.
Generative AI ensures smart processes in the everyday routine
Thanks to AI, food producers not only have the opportunity to solve complicated quality control tasks. Generative AI models that are trained using large data sets, can also help develop optimised recipes or suggest alternative raw materials.
All lectures on AI and other industry-relevant themes can be found in the event database of ProSweets Cologne: Event search at ProSweets Cologne 2025 .
ProSweets Cologne – The international supplier fair for the sweets and snacks industry will be held in Cologne, Germany 02.02. – 05.02.2025.