Machine vision tops sensors in flexibility for Ford body panel selection
Vision without code writing
A flexible user environment makes it possible to set up virtually any inspection application graphically without writing a line of code. Working from an image of the part, the user begins by finding the vision system on the network and is guided through triggering the vision system and setting up the scale and nonlinear calibrations. The user can select from a library of vision tools to inspect the part. The user selects the data to be sent and the protocol for communicating with a PLC, robot, or human machine interface (HMI) for data collection and archiving. In the deployment mode, tool graphics, a results table, and a filmstrip control are available for validating and troubleshooting the application. The cameras are contained in a 75 mm by 55 mm by 47 mm IP67 package designed to survive in the factory environment.
In current applications, the camera is stationary and the robot moves the part into position for inspection. Future applications also will use the robot to move the vision system into position to inspect stationary body panels. The number and orientation of the studs determines how many cameras are required to inspect all of the studs. Current applications include the cowl and dashboard assembly and the left and right wheel housings. There are 15 to 17 studs on variants of the cowl and dash assembly and 10 to 12 studs on variants of the wheelhouse. Each of these panels is inspected with two vision systems.
The vision systems are programmable so they can accommodate new models and design changes with a simple program change.
The camera connects to either the robot or the PLC using the EtherNet/IP protocol. The PLC or robot tells the camera which model is being inspected and which program to use. The robot positions the part in front of the camera or cameras and the robot or PLC sends a signal to the camera or cameras to acquire an image. The camera inspects the part and based on the program determines whether the part passes or fails the inspection. The camera then sends a signal to the robot or PLC. If the part fails the inspection, then the PLC signals an operator to replace the bad panel.
Integrator develops application
Each application is implemented by a vision integrator who makes the decision on the best lighting and vision tools for the application. Two approaches have been used to date. One is based on the blob tool, which recognizes an object based on its shape. The second, based on the histogram tool, compares the graphical representation of the tonal distribution of the digital image to the saved representation of a good part. The vision systems also are used to read a 2D barcode on the body. The barcode is passed to another system that checks to ensure there are no open issues with the vehicle before it is released from the body shop.
“The initial cost of purchasing and setting up a vision system is higher than a dozen proximity sensors,” Vallade said. “However, proximity sensors generate downstream expenses, such as the cost of replacement sensors and the labor and downtime required for maintenance. We also need to consider the extra work required to prepare for a design change for new variants as well as the changeover that may be required when switching from one variant to another. By switching to machine vision we have substantially reduced the downstream costs by installing a noncontact inspection system that will last for many years without requiring any significant maintenance. The vision systems are programmable so they can accommodate new models and design changes with a simple program change. The bottom line is that machine vision will substantially reduce our overall inspection costs.”
- By John Lewis, market development manager, Cognex Corp. Edited by Mark T. Hoske, content manager, CFE Media, Control Engineering and Plant Engineering, firstname.lastname@example.org.
See related links below for machine vision and automotive manufacturing.
- Ford improved flexibility by switching from sensors to machine vision for body panel inspection.
- Noncontact machine vision inspection system avoids proximity sensor maintenance, reducing overall inspection costs.
- Vision systems accommodate new models and design changes with a simple program change.
Do you look at lifecycle costs, including upgrades and maintenance, when choosing automation technologies?
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