Agristo partnered with PolySense to streamline quality control with the Virtual Quality Assistant (VQA). By integrating intelligent sensors and user-friendly software, the VQA empowers engineers to detect issues quickly, optimize processes, and reduce waste in real-time. This innovative solution aligns with Agristo's sustainability goals while ensuring top-notch product quality and customer satisfaction.
Agristo - world-leader in frozen French fries and a frontrunner on innovation
Agristo, based in the heart of West-Flanders, Belgium, is a family-owned company specializing in the production of frozen French fries and other potato dishes. As a leading global player with multiple production sites internationally, Agristo serves over 540 private label customers across 130 countries. Their annual production exceeds a substantial 900,000 tons of finished products and the company is growing bigger every year.
Offering a diverse range of over 100 deep-fried potato products, Agristo collaborates closely with clients to co-create customized offerings. The company prioritizes three key pillars: delivering added value to clients, a supportive environment for employees, and investing in a sustainable future for the company.
Keeping quality high for large production volumes
To ensure high-quality products for their vast customer base, the quality control team is a cornerstone within the company’s manufacturing facilities. This team performed an hourly manual inspection of the fries at different stages in the production process. This inspection is then used to adjust the process parameters in order to increase the overall quality of the end products.
As this is a very labour intensive task, the quality team was in need of a more efficient solution that could support them in their day-to-day jobs: ensuring the quality of their customer’s bright yellow business.
The combination of their technical expertise and flexibility allows us to reach great results, fast. They provide the perfect tools for deploying artificial intelligence to gain real impact.
Introducing the Agristo Virtual Quality Assistant
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As a support for Agristo’s quality team, PolySense developed the Virtual Quality Assistant (VQA). This platform assists the quality engineers in the early detection of quality anomalies in production. The Virtual Quality Assistant consists of an intelligent sensor setup and a custom integrated application.
The intelligent sensor setup are the quality engineers’ eyes on the production line. We designed a hardware module tailored to the production line that can record the necessary data. Based on depth information and images, our AI model can make an accurate prediction of the length, defects, quality class, … for the large variety of products Agristo produces. Special care was taken to ensure food safety, robustness and ease of use when designing this module.
The integrated application forms the interface between the quality engineers and the production line. It is fully integrated with Agristo’s ERP system to make it easier for the users to retrieve the relevant information about the current order. The Virtual Quality Assistant reports real-time statistics about the quality of the batch that is produced at that time. This consists of the french fry length, the type of defects, colour, etc. In short, everything the quality engineer requires to quickly intervene when necessary. The insights of Agristo's quality engineers played a pivotal role in ensuring a seamless user experience for the integrated application.
Reducing waste streams by 5% and saving 1 hour each day
Together, the intelligent sensor setup and the integrated application form the building blocks of our solution for Agristo. The Virtual Quality Assistant provides more information for the quality engineers to make quick informed decisions based on the insights the dashboard provides them with.
Instead of discrete hourly inspections and measurements, the quality team can now act on the continuous information from the Virtual Quality Assistant. This not only improves the overall quality of the production, but also reduces the amount of out-of-spec end products reducing the amount of waste the production line creates.
