Vision-based quality control system in FMCG manufacturing

Label verification tool needed

Bunge Polska Sp. z o.o. in Kruszwica, a manufacturer of food-grade vegetable fats, was looking to avoid errors during the printing process of labeling its products, so they sought an effective solution to verify that labels aligned with approved templates. A solution was found in LabelScan.

The solution: a dedicated LabelScan system

To meet the client’s needs, we designed a system for vision-based label validation (LabelScan). Solwit proposed a solution based on AI and more specifically Computer Vision, allowing for the instant testing of a label sample. The batch standard can therefore be met for compliance already on the production line.

The system receives a graphic file with the sample and a scan of the sample under test. It takes a few seconds on average for the operator to receive information about the test label conformity and a preview of the sample with marked defects. The solution is designed to draw the operator’s attention to significant discrepancies, e.g., wrong package capacity, barcode error, typo or missing space in the text, and missing or redundant graphic elements. Most importantly, the system does not involve employees in non-compliances that are insignificant for the manufacturer (slight color deviations or typical features of the label production process).

Solwit used Python and .NET technologies to implement the project. Within the AI engine responsible for image analysis, Computer Vision techniques implemented in the OpenCV and scikit-image libraries were used. We organized the technical infrastructure with the client at the production site in Kruszwica and the Data Centre in Geneva. The system has already been implemented and runs around the clock at six control stations. Aside from its primary function, it will automatically report to management all completed sample tests and provide access to archived results up to one year back.

 

During the bidding process, we presented Bunge with a Proof of Concept containing the main functionality of the system. This way, the client knew from the very beginning what the target value of our system would be. It was a collaborative effort – Bunge representatives were involved in fine-tuning the functionalities so that they met their actual needs. By presenting the work on a real product, the effects could be seen and tested, not just read about how a certain section of the documentation works.

Artur Zawadzki, Delivery Manager, Solwit

Automation of the verification process

A total of three production lines and an additional station at the oil bottling plant were integrated with LabelScan in December 2022. We installed and launched the backend application on a server at the customer’s premises and the frontend application on four PC stations. After implementation, the label dispenser employee can immediately confirm that the batch correlates with the planned production pattern. Prior to this, they verified the labels on the machine against the workbook template when filling them in. LabelScan makes the whole process automated, speedy, and accurate, up to 99.9%. With LabelScan, Bunge safeguards against costly downtime due to misprints and the resulting need to remove faulty labels and re-label products.

Solwit has successfully delivered a solution for us that profoundly enhances the efficiency of several departments. LabelScan was an IT project implemented by many different teams as stakeholders at Bunge. Despite the high demands, both the design and implementation were completed within the stipulated timeline and with the utmost quality. Special mention should be given to the programming team – thanks to their knowledge and experience, the system prevents costly downtime and facilitates repetitive tasks for crew members.

Przemysław Stępniak, Plant Managing Director, Bunge Sp. z o.o.

Thanks to LabelScan, Bunge protects itself against costly downtime related to incorrect printouts, and the need to remove defective labels and re-stick products.

 

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Vision-based quality control system in FMCG manufacturing
Industry and country
manufacturing
Poland
Technologies
Python
.NET
OpenCV
Platforms
desktop app
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