Automated Food Inspection
Sightline systems are non-contact inspection systems that use a series of high-speed cameras and imaging software to detect and measure random objects as they move along a conveyor belt.Virtually any size, shape or color attribute can be extracted from the object images and converted into standard units, providing real-time 100% inspection of any production line.
Buns/Bread/Baked Goods
The manufacture of baked goods provides many challenges since there are a multitude of input variables that can affect product quality.
Tortillas/Flatbread/Pizza
For these products, a series of special measurements allow manufacturers to properly quantify critical quality attributes.
Cookies/Crackers
The ability to rapidly quantify critical product attributes make automated inspection a useful tool for cookie/cracker and bar customers both as over-the-line and off-line (lab) inspection.
Other Food Products
Virtually any food product can be measured using Sightline’s 2D/3D/color imaging technology, either directly during the production process (Over-Line / In-Line) or using a Benchtop Inspection System (Off-Line).
Generate Trusted Product Quality Data
Automated inspection provides a repeatable and analytical method for generating product quality data, eliminating measurement errors caused by operator bias, varying measurement techniques and ‘qualitative’ analysis (e.g. blotchy). It can also provide measurements that would otherwise be impossible to quantify such as bottom color, topping coverage and product volume.
Achieve Product Quality
Sightline systems allows food manufacturers to continually ensure the quality of their products at any line speed and any time of day. The ability to measure and quantify key attributes for every object, combined with the ability to automatically remove defective objects, is an invaluable tool for product quality, process improvement and cost reductions.
Use Historical Data to Improve Productivity and Efficiency
Since all measurement data is stored for every object, historical data analysis is also a useful tool in the identification of processing problems and opportunities for improvements. Key productivity data such as throughput, downtime and changeover time is also stored along with product measurement data, allowing for additional productivity and efficiency analysis.
