3D inspection of finished product and packaging
Food quality verification processes absolutely require dynamic vision solutions. These processes include:
- Defect detection and surface validation
- Identification of cakes, individual cakes, candies and cookies
- Checking the height of the icing
- Checking volume and flatness
Precise 3D measurements
Top quality guarantee
With In-Sight software, you can perform precise 3D measurements to ensure the quality of your products. You will leave no room for error by measuring dimensions and volumes with exceptional precision. This means better quality products and happier customers.
Our In-Sight software is designed so you can master it quickly, even without advanced technical skills. Quickly set up reference planes and measure your objects with ease. You'll save time and money by avoiding hours of costly training.
Unrivaled reading performance
Total safety with the 3D laser
The In-Sight 3D-L4000 delivers cutting-edge 3D laser scanning without compromising security. You'll benefit from more accurate measurements thanks to improved light projection, even in the presence of debris. This is a major advance that guarantees you maximum efficiency without risk for your operators.
Integrating 3D measurements and 2D image chains provides food producers with an efficient way to maintain their quality goals while avoiding product recalls.
Quality inspection of chocolate boxes
Compliance with strict standards Identification of physical defects Identification of irregularities
Automated Meat and Poultry Inspection
Accuracy during visual classification of already packaged meat Visual identification of plastic or polystyrene foam Rapid detection of physical contamination elements
Detection of the subtlety and variability of possible defects as well as variation in acceptable appearance Achieving a level of quality that cannot be matched by other types of visual inspection
Inspection of coffee beans
Identification of batches of grains confirmed before their inventory Verification of detection of physical contaminants, such as plant matter, stones, etc. Acceptance of variation in overall differences between coffee bean varieties
Inspection and sorting of nuts
Distinction between acceptable forms and unacceptable states Rapid classification of nuts as acceptable or unacceptable Neither manual inspection nor other forms of machine vision can achieve the same speed and accuracy in this task
Detect volume and portion errors to maximize yield and reduce waste Measuring the volume of food products during assembly to check portion size
Foreign body detection
Intervention of contamination and foreign bodies, e.g. air pockets, dust, particles, hairs, etc. Defect detection in high-speed production environments Locate, analyze and classify complex contamination issues in real-time to prevent contact of contaminants in the supply chain on high-volume lines
Verification of product uniformity
Identification of packet patterns and stamps, despite changes in orientation, angle, lighting, etc. Rejection of damaged and broken products before packaging or distribution