Before applying cement, the smooth side of the tread surface must be inspected to ensure the quality adhesion of the tread to a tire carcass. Although a human inspector can easily find defects like blisters and cracks, small defects can be a challenge, and other surface defect anomalies may require shifting positions to find variation in surface sheen.
Our team shadowed human inspectors while collecting images of the product, annotated images, and then an image-based deep learning model was developed to detect surface anomalies. Through further data collection, annotation, and model iterations, the system gained the ability to classify the surface anomalies into several categories. Traditional vision (rule-based) algorithms were added to established pass/fail criteria based on shape, size, and brightness for each classification, thus reducing the need for 100% human inspection.
The existing smart sensor did not have the tools to determine if label placement was out of spec. Quality Department requested the ability to make sure that the Lot/Date code is present.
The line was moved from another facility to a local one, and no documentation could be found. The existing controls system was reverse engineered, and the vision camera was upgraded to a Cognex InSight that mimicked the old system. Retrofit required the removal of some of the existing material handling components, which were removed, modified, and installed over a long weekend. The system was successfully brought online for the start of production.
Prior to a tray of vials being loaded in the freeze dryer, the number of vials needs to be counted and documented. Depending on the size of the vials, the number of vials on a tray can range from 100 to 225. Descrepencies between the manual count and actual count occur from time to time.
Due to the need for a continuous laminar airflow on the vials within the cleanroom, the vision system components could not be mounted directly above the vial tray. High-intensity side lights were deployed on the side of the tray. The vials would act as a light pipe allowing for sufficient contrast for the smart camera to identify and count the vials. The HMI of the software provided the Operator with an overlay for each bottle located, and a foot pedal allowed the Operator to acknowledge the count. The images were archived, and a PDF-generated report was saved to network storage at the end of the batch.
A Temp labor team assembled packaging for box displays for a Trading Card game. Occasionally cards or accessories were incorrect or missing.
The product enters a multicamera light tunnel and a QA engineer uses a Wizard to draw ROIs for each card and accessory. Cognex VisionPro's PatMax was used for its robust pattern matching algorithms. The system would stop the conveyor once it exited the light tunnel if there was a mismatch or no match, and turn on a stack light.
A filler machine adds powder to a dose pouch. If the douce pouch is not properly opened, then the product is spilled onto the bottom of the machine.
Cognex InSight program was developed to profile the outside shape of the dose pouch. If the center gap distance and area were too small then the filling is skipped for that dose pouch.
2D barcode label was applied to the end of a syringe. Labels that are wrong or placement is out of specifications need to be rejected.
Cognex Smart camera was added to an existing label applicator machine. The syringe was rotated and 4 images were acquired. The 2D matrix on the barcode was verified against the SKU read in from the PLC. The label position was gauged relative to the tip of the syringe and all 4 images were used to calculate the label skew.
Catheters are placed into a vaccuum-formed pouch and then sealed to Tyvek. A CAPA event required automated inspection of catheter packaging inspection to ensure no portion of the catheter made it past the seal.
Multiple images were rapidly acquired as the product indexed past the sealing process and the seal zones were analyzed with a Cognex Smart Camera.
Car interiors are often customized for their material, trim, and user features. Variations may be subtle and batch runs are small. An end-of-line inspection system is needed to ensure the product that was assembled matches the build ticket.
A camera with a bright field and dark field configuration was mounted to the end of an ABB robot. The operator loads an assembled car door interior onto an open nest and presses the Inspect bottom. The robot would move to 20 different locations on the backside of the car door interior, triggering the camera/lights, and then requested the operator to rotate the fixture. The robot then moved to 6 different locations, triggering the camera/lights for each.
A mock display is presented to the Operator for pass/fail of all zones. The operator had the ability to select a zone to see the image taken and individual pass/fail results for each Poka-Yoke item.
After the bearing raceway has been machined to a sized blank, the possibility exists that the surface may have underfills, pitting, or other blemishes. Such non-conformances need to be removed and repaired before the additional value is added to the product.
The product is placed into an encoder roller system via an overhead robotic system and is imaged with a line scan camera. If variations in the surface finish are detected, the product is moved to a secondary inspection area, other wise it is moved onto the next step in the process.
A robotic system applies Loctite to various holes on an engine block. Insufficient application of Loctite can create quality issues.
An additive in the Loctite causes it to fluoresce if illuminated with UV lighting. Cognex InSight camera with a Blue bandpass filter image the Loctite application for presence and bead width and continuity.
A fuse block assembly for a car or truck has similar frames, but what goes into them can vary. A component can easily be missed, such as a fuse or diode or the wrong relay model installed.
A GUI was developed to allow an Engineer to train a new component (color, pattern matching, OCR) and add it to a component family. Once populated with components, an Engineer can create a product SKU and create a Region of Interests (ROIs) for each component location on the fuse block. The engineer can choose the allowed orientation of the component for the ROI.
With a fully configured product, an Operator can recall the SKU from a part list and batch inspect multiple fuse blocks. Any component that is missing, in the wrong orientation, pattern score is too low, or OCR is mismatched, then the ROI is highlighted in red. Components that pass are highlighted in green.
Key blanks for major retailers are plated, stamped and channels cut. Non-conformances can include poor plating, poor stamping, misaligned stamping, and misaligned channels.
The system was trained with the average composite image of 10 or more keys. Cognex PatInspect and additional image processing were used to determine the difference image, then blob analysis determined pass/fail result.
Opiate Lozenges are sonic welded onto a plastic stick, inspected, and transferred to a packaging tray. An embossed number on the lozenge indicates the dosage of the product. The wrong or unreadable embossed number is considered a non-conformance. A chipped or cracked lozenge is also considered a non-conformance.
Cognex VisionPro was used to pattern match the embossed number; too low scores were rejected. Image processing tools masked out the embossed number, and edge detection algorithms were used to identify cracks/chips.
The product is placed by a robot into a thermoformed package. If the product is not properly placed into the individual pockets it can create a problem with the top foil seal.
Cognex InSight and pattern matching were used to verify the product was seated correctly in the individual pockets. The product line was stopped for non-conformance.
Brazing paste is dispensed onto a sprocket gear before entering the oven. Too much, too little, or not in the correct position will cause a poor weld.
A Cognex InSight Camera was used to determine the orientation of the sprocket with pattern matching and provide offset information to the dispensing robot. The robot would dispense two blobs of paste between the teeth of the sprocket on opposite sides. After the application, the smart camera applied blob analysis to verify the amount of brazing paste dispense was within tolerance.
From new to end of life, welding tips used to spot weld the housing to the band create varied results. From time to time, a weld would fail to fully engage and would produce a light or no weld.
5000 images were collected and annotated, then applied to a neural network-based descision engine (predecessor to modern deep learning algrothims). System performed well after new tips were broken in after 2000 cycles. (Average life cylce of tips 35k - 40k)
Tablet press machines over time require routine maintenance, and scheduling downtime can be a challenge. Having chipping or caping the tablet is considered a non-conformance and should be separated.
Cognex InSight camera located and fixtured image processing tools on the tablet. Blob detection tools were then used to locate edges in areas that should be quiet. Results were signaled to the PLC.
On pills/tablets with a surface coating, contract pharmaceutical manufacturers will print a brand/ID instead of making an imprint. Missing text or faded print is considered a non-conformance.
Cognex InSight smart camera located the print, and pattern matching scores were determined for individual characters. Pattern match scores below a specific threshold were rejected.
Supplier for the machines that manufacture the Permanent Residency Cards needed to ensure that the text printed on the card matches what is contained in the database. It was also to ensure the person’s face was printed clearly, and verify the presence of several security features.
Standard lighting techniques and Optical Character Recognition routines where used to validate the text and data that was contained in the database. Image correlation was used to validate the person’s face printed on the cards. Multiple different lighting techniques and LED wavelengths were used with different image processing alghrothims to verify the presence of all security features.
Supplier for the machines that manufacture the Driver’s Licenses needed to ensure the text printed on the card matched what is contained in the database. Also needed to ensure the person’s face was printed clearly, and verify presence of the engraved birth date on the card.
Standard lighting techniques and Optical Character Recognition routines where used to validate the text and data that was contained in the database. Image correlation was used to validate the person’s face printed on the cards. Photometric stereo imaging technique with IR LED lights was used to extract the engraving and filter out the print on the driver’s license.
Dashboard displays manufactured by automotive suppliers are hand assembled with different Legend Tags (door open, oil temp, washer fluid low, etc.). Before the product is packaged and shipped for assembly into a vehicle, 100% inspection is required to prevent quality chargebacks.
PC-based vision system reads the 2D barcode on the cluster assembly and queries a database. The database provides information on what Legend tags are to be installed in each of the 10 locations. Using pre-trained patterns, the system verifies all 10 locations on the cluster and prompts the Operator of any mismatches.
Dashboard displays manufactured by automotive suppliers must have all the gauges (speedometer, tachometer, engine temp, etc.) calibrated before shipping.
The operator places the product into a test docking station, and the gauge is provided a signal for 3 different values. The PC-based vision system determines the angle of the needle on the gauge and provides the value back to the test docking station. The 3 data points are used to calibrate the gauge, and values are saved to the EPROM of the dashboard display.
Vinyl floor manufacturer was looking to increase the consistency of their product by detecting foreign color chips, shade breaks, and "eye poppers." Vinyl flooring is made by grinding up various color chips, heating them, and rolling them flat. Since broken tiles are often ground and put back in the mix, any tiles left over from the previous batch run could introduce undesirable variances.
A PC-based vision system segmented the image for the tile. During the training, the process scanned and identified all the grouped colored signatures, including the background average color—tiles with background shade breaks and non-conformances were rejected. After multiple consecutive rejects, an operator was alerted.
An Automotive manufacturer needed to verify the correct roof has been placed on the vehicle prior to robotic welding.
PC-based Vision system identified key features of 6 different possible roof configurations and verified a match based on the VIN barcode.
An Automotive manufacturer needed to verify the correct fender has been placed on the vehicle prior to robotic welding.
PC-based Vision system identified key features of 4 different possible fender configurations and verified a match based on the VIN barcode.
Molded fenders made from thermoplastic olefins (TPO) require an adhesion promoter (Adpro) prior to the application of automotive paint.
A PC-Based vision system projected a laser line onto the TPO fender. A raw fender would create a diffraction pattern when reflecting the laser line, whereas the application of Adpro creates a diffuse reflection. Image processing analysis detected the signature difference between the two, and the system would stop the line if a non-conformance were detected.
Fenders are welded to a truck bed by welding robots. Misaligned fenders need to be detected and corrected before the truck bed proceeds to the next step in the process.
The PC-Based vision system used structured light to detect and measure fender location on the truck bed. Rejects were flagged, and an alert was raised to the Operator.
Metal truck panels after forming enter into a rust inhibitor dip tank. Panels that are not properly secured can "float" off the carriage into the dip tank. Subsequence carriage entering into the dip tank can have their panels damaged.
A PC-based vision system was used to verify all the locking pins holding panels to the carriage were in the correct position. If an improper position locking pin was detected, the line was stopped, and an alarm was raised.