AI IN FOOD INDUSTRY
A label inspection system based on Computer Vision
Artificial Intelligence is transforming production processes in the FMCG sector, enabling automation, reducing errors, and significantly enhancing operational efficiency. In the domain of quality control, AI not only accelerates verification processes but also achieves a level of precision unattainable through manual methods. We implemented such an approach for one of the leading food manufacturers in Europe.
For a producer of vegetable oils and margarines, we developed a comprehensive AI-based solution that analyzes label images in real time. The LabelScan system leverages Computer Vision techniques to automatically detect deviations from approved label templates and alerts operators only to relevant discrepancies—eliminating the risk of errors and production downtime.
Challenge
Eliminating labeling errors without slowing down the production line.
Solution
Deployment of the AI- and Computer Vision-powered LabelScan system for automatic and precise label verification directly on the production line.
Benefits
- Real-time label analysis – results in seconds
- Accuracy up to 99.9%
- Reduced downtime and risk of non-compliance
- Intelligent differentiation between critical and non-critical errors
- Process automation – minimized manual labor
Intelligent quality control – The role of AI in addressing the challenge
Traditional label verification systems often rely on manual inspection or trigger alerts for even the slightest deviations, regardless of their relevance to compliance. This leads to unnecessary production stoppages, increased operator involvement, and higher operational costs. With the introduction of artificial intelligence, it became possible to design a system that learns patterns, distinguishes between critical and minor issues, and operates fully autonomously—without interrupting the production line. For the client, this represented a breakthrough in quality management and operational efficiency.
AI technologies and tools applied in the project
The core challenge involved the risk of mislabeled products reaching the market. The client sought a solution that would detect graphical inconsistencies at an early stage to ensure compliance with approved designs and avoid potential costs associated with labeling errors. In response, we developed a tailored solution incorporating advanced AI techniques, particularly image comparison algorithms rooted in Machine Learning. The implemented model enables operators to efficiently analyze scanned labels by comparing them to a reference template and visually highlighting any deviations. The system acts as a specialized tool supporting final quality control—delivering efficient, rapid, and automated verification during the packaging and distribution stages.
Tangible results – client and user benefits
The implementation of the AI-powered solution delivered measurable outcomes. The label verification process was reduced to just a few seconds, eliminating the need for manual inspection. With an accuracy rate reaching 99.9%, the system has virtually eliminated labeling errors that could lead to product recalls or regulatory penalties. Routine tasks were removed from operators’ responsibilities, allowing them to focus on situations that truly require human intervention. As a result, the client gained enhanced quality control, notable operational savings, and a competitive advantage driven by improved production efficiency.
