There are numerous elements in the production of chicken that can affect quality and reliability. Employing KPM Analytics vision inspection technologies, such as systems from Sightline Process Control with integrated measura® real-time inspection software, configurable with user-defined parameters, to analyze important product qualities allows users to swiftly detect and respond to production concerns.
Height Map of Raw Chicken Strip. Image Credit: KPM Analytics
Image Credit: KPM Analytics
The measura® Analytics Software was created to connect directly to the data provided by KPM Analytics and the Sightline Process Control brand, offering a graphical overview of operations as well as quick access to past production data based on a raw object or minute data.
Users can make time-sensitive choices to ensure the most effective operation, increase quality and save costs by having immediate and quick access to production and QA metrics.
Image Credit: KPM Analytics, Inc.
Vision Inspection technology can evaluate virtually any food product, either instantly during the process of production (Over-Line/In-Line) or via a Benchtop Inspection System (Off-Line).
Smart Thickness. Image Credit: KPM Analytics
2D Measurements. Image Credit: KPM Analytics
Fat Area Analysis. Image Credit: KPM Analytics
Blood Spot Detection. Image Credit: KPM Analytics
The following include some of the raw poultry-specific measures available.
Table 1. Overhead 2D Analysis. Source: KPM Analytics
||The length of the object as measured down the center of the long axis.
|Dual Caliper Width
||The summation of the longest widths of the object as measured perpendicular to the Caliper Length.
|Keel Location, Length, Angle
||The positioning of the keel relative to the caliper length of the object including the keel length and angle at which the keel intersects the line defining the Caliper Length of the object.
||The total surface area of the object (mm2 or in2) that can be compared to minimum and maximum limits for portion control.
||The percentage of the surface area with color anomalies (i.e. blood spots, dark meat, or PAA discoloration).
||The length and width of a contour defect resulting from excess paring during separation of cuts.
||The average color of the product across the surface area.
|Fat % Area
||The percentage area of the object that is fat-colored (i.e. white).
||The quantity of striation lines and percentage of the object’s surface area covered by striation.
Table 2. Height 3D Analysis. Source: KPM Analytics
|Min, Max, Avg, & Adaptive Thickness
||The lowest, highest, average and filtered height of the object when resting on a flat surface; calculated by taking the average of the ‘N’ highest height points measured on the top surface (N is user-configurable).
|Volume & Weight
||The calculated volume of the object as determined by the surface area and mean height. Can be used with average density entered into the system to derive predicted weight.
||The curvature of the top surface on the product; measured by calculating the vertical change between the thickest region and the tail of the keel.
This information has been sourced, reviewed and adapted from materials provided by KPM Analytics.
For more information on this source, please visit KPM Analytics.