FOOD & BEVERAGE
ADVANCING FOOD SAFETY WITH AI
A new report released by BCC Research indicates that AI technology applied to areas such as contaminant detection, traceability and compliance is projected to grow at a CAGR of 30.9 per cent by 2030. Anticipated to be valued at USD$13.7 billion, this will revolutionise food safety and strengthen quality control reports Phil Brown, sales director at Fortress Technology Europe.
M
achine vision is integral to this key trend. Forming part of a larger inspection system, adding vision capabilities to existing technology, for example metal detection or X-ray, strengthens quality control by capturing an image and processing it against set quality control parameters. In inspection technology, vision is usually deployed for label verification, rather than food surface defects. For example, it can inspect the top and bottom of the pack to ensure that labels and promotional offer stickers are correctly placed and
feature dates. The result is greater compliance with legislative food labelling rules.
AI THAT SUPPORTS FOOD INSPECTION EFFICIENCY
One of the most valuable ways to contribute to a safer, more secure and sustainable food supply chain, as well as maintain a competitive edge in the industry, is through process and operational optimisation. Leveraging smarter technology and predictive analytic tools can help to create a safer, digitised and more traceable food system.
There are various inspection configurations available to food processors, from standalone metal detectors, checkweighers, x-ray and vision systems, to combination systems in any arrangement of these technologies. One of the greatest benefits of combination units is that the data centre can be integrated, rather than trying to tie multiple disparate database formats together. Fortress is already using its proprietary data software package, Contact 4.0, across its metal detection and checkweighing technologies. It enables processors to review, collect data and securely oversee the performance of multiple Fortress metal detectors, checkweighers or combination inspection machines connected on the same network.
Deployment of this type of data reporting provides context to support rule-based machine learning. It also enhances human decision-making through the extraction and interpretation of data.
COMPLEMENTARY INSPECTION TECHNOLOGIES
Integrating multiple inspection technologies into 18 Winter 2025/2026 UKManufacturing
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