Q -Bake tortilla - Arr-Tech

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General description EyePro System, a leading company in the machine vision field, is proud to present Q-Bake , a family of fully automated inspection systems specifically designed for the baking industry. The Q-Bake product line represents the state of the art of vision technology for the inspection of baked goods. These machines can be used for the on-line and off-line control and measurement of color, shape, surface and volume of bread, buns, biscuits, crackers, tortillas and many other baked products. a specific solution for tHe tortilla industry Thanks to the use of a modular hardware and software architecture, EyePro System has designed a customized version of its inspection machine for the tortilla manufacturer. The Q-Bake Tortilla inspection system can measure the size, shape and color characteristics of tortillas. The 2D/Shape measurements are displayed and stored in mm or inches. Thanks to the use of the TRUE COLOR TECHNOLOGY, the Q-Bake Tortilla system carries out color measurements (baking degree, toast marks, light/dark spots and foreign material) using standard color units (CIE-Lab or BCU). The baking status color measurements can be used for the real time control of the oven using the exclusive EyePro OVEN FEEdbaCk CONTROL UNIT.
The Q-Bake Tortilla system, which is typically installed on a tortilla line between the cooling system and the counter/stacker machine, performs 100% product inspection and comprises: • Processor Control Unit with touch screen display • Inspection Unit with integrated TRUE COLOR CaMERa HEad • Inspection conveyor belt (modular belt type) • Pneumatic rejection sub-system for the automatic removal of defective products The system checks and classifies the conformity of the products inspected using previously learned models. An indefinite number of models can be defined. A semi-automatic selflearning procedure sets the characteristics of the model. For the configuration of a new model, the user has only to acquire a few images of good samples, use the self learning tool then set the tolerances for each control. During the inspection sessions, the products classified as defective or out of tolerance can be automatically rejected from the line. The graphical user interface displays detailed information such as the inspection data (start/stop time, the number of controlled, good and defective products), the total and the partial defect distributions, the measurement trends and histograms, as well as the images of the last 20 faulty products along with their measurements. For each inspection batch a report is automatically generated which contains all the inspection data. The reports can be printed, viewed and exported through a LAN connection. The measurement data is also stored on a standard database for off-line statistical analysis. The system has several hardware and software tools for calibration, diagnostics and automatic compensation for different lighting conditions. system specifications MEaSUREMENT (aCCURaCY): • Minimum Diameter (0.8 mm – 0.03”) • Maximum Diameter (0.8 mm – 0.03”) • Mean Diameter (0.8 mm – 0.03”) • Roundness (0.5 %) • Shape likeness (% of likeness compared with a pre-learned shape of target product) • Bake color (without toast points) (0.2 ∆E - 0.02 BCU) • Color evenness (0.5 %) • Bake difference from mean (0.2 ∆E – 0.02 BCU) • Toast points color (0.2 ∆E – 0.02 BCU) • Toast points quantity (0.5 %) • Toast points distribution (0.5 %) dEFECT dETECTION CaPabILITIES: • Out of spec products (compared with the defined tolerances on the measurements) • Doubles / Clusters • Straight edges / Folds • Bites / Dents / Holes • Toast points voids • Light spots / Darks spots • Foreign material
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Q -Bake tortilla - Arr-Tech

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