Contamination of food by plastic fragments is a growing concern within the poultry industry. Plastic contamination can either be accidental, for example if a worker’s latex glove is torn or an employee loses a ring down a processing line, or deliberate. Determining both source and composition of plastic fragments in poultry products are vitally important to ensure corrective actions are taken to eliminate contamination from reoccurring.
Foreign object detection and rejection by a poultry processing plant is essential to maintain and increase the quality of their products. Today most food manufacturers have inspection systems in place that inspect products as they pass down production lines.
Metal detectors help poultry food processors keep metal fragments from ending up in finished products, but these detectors can’t identify plastic and other foreign objects.
Challenges
The poultry industry is concerned about the amount of plastic found in their processed products. Plastic-contaminated meat is particularly dangerous, because these pieces of plastic are hard to distinguish in meat products.
The product stream moves quickly (about 12 feet per second, or eight miles per hour or more). If manual inspectors blink or look away for even a second, they might miss something.
When plastic contamination occurs, it’s expensive for companies to deal with it. This leads to product recalls and logistical issues. It can have a negative impact on a company’s image and can cause consumers to lose confidence in the brand.
Solution
Poultry processing companies need computer-vision solutions to detect extraneous elements in their finished food products. It is very important to locate such objects, then remove them before distribution or sale, but it needs to be digitized.
Computer Vision solutions are capable of classifying and detecting objects that are of same size or larger than the targeted material using its sophisticated color discrimination algorithms.
Solution requires minimal manufacturing data and can be trained in less than an hour. The CV cameras work by detecting images of a good product and asking for it to be highlighted. This is repeated for a number of products so that the computer vision solution learns desired shape and characteristics of product and foreign objects.
When the CV cameras recognize a foreign object. It takes a picture and an alarm is triggered to remove that product from the line. Although this solution can determine all colors, it was tested on blue and green objects. Blue plastic is an industry-standard, it is used to make equipment and containers used in food processing.
Visionify.ai’s Foreign Body Detection Solution is an innovative solution for detecting foreign bodies in food manufacturing and processing. Advanced imaging systems analyze color, size, shape, and temperature of foreign bodies moving on a conveyor belt without human intervention. These systems provide qualitative information along with quantitative data with respect to size, shape, and location of foreign bodies detected in food products.
