An innovative implementation of AI in the food industry will be presented at the Prosweets Cologne 2025 fairgrounds to improve 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. From the connection of the machine to the precise recording and administration of operating and machine data, through to the dynamic visualization and analysis – 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, with regards to this year’s highlights of the leading business platform for the global suppliers of the sweets and snacks industry. Instead of “just” recording data, AI can analyze trends and predict future results. By using advanced algorithms it reveals hitherto hidden inefficiencies and delivers recommendations of action to increase “the reliability and flexibility of the production and optimize the use of resources.”
Guido Hentschke, Director, ProSweets Cologne
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 Prosweets Cologne 2025 offer an unprecedented level of precision – for example in recognizing defects in biscuits, wafers, and crackers. Whether round or square, sweet or savory, made of wheat or oats: Even slight deviations on complex surfaces are detected on the conveyor belt directly after leaving the continuous oven – this minimizes production stoppages and waste and goes hand in hand with the producers’ commitment towards more sustainability.
Visual quality control intelligently optimized
The special feature is that AI assesses the products individually and allocates quality indicators. Holes, breakages, insufficient coating, and oozing chocolate are labeled 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 recognize cracks or color 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 can scan hundreds of products a minute continually and find tiny flaws or contaminations, which could impair the quality of the food. Artificial Intelligence 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 is tasks that can no longer be solely solved using sensors that work in the visible wavelength range. Here, the hyperspectral image processing of the Austrian company, Insort, reaches down to the 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 like the Sherlock Hypernova by Insort 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 optimized recipes or suggest alternative raw materials. The company specializes in the introduction of various SAP products and develops intelligent applications to solve local customer needs. One of the results of the growing demand for AI applications is above all the increased interest in the SAP Business Technology Platform (BTP).
“They enable combinations of ingredients and production methods to be discovered that meet the requirements of the consumers more readily and which are at the same time more cost-efficient.”
Pierre Wiese, Managing Director, Solvia Digital Solutions
“SAP BTP offers a host of options for putting generative artificial intelligence to targeted use.”
Dirk Nolte, Head of ERP Consulting (SAP), Solvia Digital Solutions
An example of such a service is the Product Finder of the Darmstadt-based company, Döhler, a supplier of natural ingredients, which will be presenting its solutions at ProSweets Cologne 2025. The tool that enables an AI-supported recipe search will be presented by Pierre Wiese and Dirk Nolte on 4 and 5 February, at 11:30 a.m. respectively in the scope of the lecture “Sweet AI – how AI supports the food and beverage industry” on the new Sweet Week – Talks & Tasting Stage. Furthermore, the two experts will explain how AI improves the customer experience at Döhler.