A machine vision inspection has a relatively simple purpose: to input a snapshot of the application, evaluate this snapshot based upon a set of given tolerances and output a “pass” or “fail” signal. This sequence is otherwise known as acquisition, analysis, and determination. One or more analysis tools within the vision system software determine whether a product passes or fails the inspection. A vision tool may also be used to perform the logical operations required to activate the vision sensor’s output, which can in turn activate an external device that diverts rejected parts from the line.
To practically apply a vision solution in food and beverage applications, the sensor is taught to identify a known “good” reference part, such as a properly filled and capped milk bottle, from a “bad” part. The system accomplishes this by comparing the application image the vision sensor acquires to the stored “good” part, then rejecting those products that demonstrate inconsistencies. For instance, in a bottle filling application, a fill tube may become loose and fall into a bottle—contaminating product and interrupting the filling process. A vision system that detects this abnormality can output a “fail” signal that stops the line, minimizing downtime by allowing the problem to be readily addressed.
Meat Package Inspection: Vision sensors can be used to verify label presence and position on high-speed packaging lines.
Color vision sensors add color differentiation to this vision system’s capabilities, so that the sensor can identify the hue variations that could mean the difference between a “good” and “bad” product. If each bottle cap in a container must be of a certain color, the sensor can verify that each colored cap is in its proper location and that all container slots are filled. A similar arrangement allows the vision sensor to inspect a box of chocolate candies—verifying that each candy, differentiated by hue, is in its designated paper nest and that all candies are intact.
To verify label presence and position on a jar or bottle, a vision sensor measures the distance from the top of the label to the neck of the container in two locations, thus confirming proper alignment and label height. Simultaneously, the sensor measures the distance from each end of the label to its associated container side. This ensures the label is within its proper horizontal alignment. A comprehensive yet efficient process, this vision inspection can save manufacturers many wasted hours and dollars due to returned or recalled product.
Recently, vision technology has been applied for confirming date/lot codes on food and beverage items. While these codes have been used in the pharmaceutical industry for years, the food and beverage industry is now using this technology more often to assist in product recalls. Vision sensors ensure the proper date/lot code has been placed on each package before shipping, so that if a recall is needed, the product can be traced back to its initial batch. Date/lot code verification simplifies identification of the faulty product and also saves manufacturers time and resources. Rather than requiring a recall of truckloads of product, the recall can be isolated to only the loads containing the faulty batch—which may only be a few pallets.
To assure food integrity, vision tools examine products for consistent color, shape, size and quality. Color vision tools allow vision sensors to inspect for matching hue and intensity, identifying the fat percentage in meat before processing or grading. Inspection and analysis tools may also be used to verify bacon strips are cut to the same size and length, or that granola bars are all of the same width and length without breakage. This quality assurance promotes customer safety and satisfaction while enhancing the user’s bottom line.