Dial-X Automated Equipment designs and builds automated inspection, assembly and material-handling equipment for a wide range of customers, including those in the pharmaceutical, automotive and consumer goods industries. It often integrates machine vision in its systems to do everything from detect part deformities to verify part presence in a finished assembly.
Recently the company built an automated connector assembly machine that included 11 PresencePLUS cameras, two spotlights, a backlight and an on-axis light from machine vision and machine safety specialist Banner Engineering Corp.
Dial-X went with multiple lighting types to accommodate the different kinds of parts being inspected.
“If we’re verifying the connector’s shape, we’ll use a backlight to create a silhouette of the product,” says Dial-X project manager Ryan Berkes said. “For verifying color, we’ll use a spotlight to highlight the front part of the connector. The on-axis light is used to mute the color of one of four internal connector parts. This allows us to measure and verify that two parts are assembled correctly.”
The machine also includes a number of EZ LIGHT indicator lights, also from Banner. These lights are most often used for highly visible machine status indication. However, in the case of the connector assembly machine, their small size and robust construction made them ideal for lighting some of the connectors’ smallest components.
According to Dial-X President Curt Bonar, his company frequently employs PresencePLUS Pro and P4 cameras in the machines it builds because of their flexibility, their small size, and the ease with which they can be integrated into a larger, more complicated system.
“We chose Banner originally because their equipment was low in cost and worked well for inspecting our customers’ products...Banner’s vision sensors offer ease of use and relatively small size, with lots of lighting accessories available, as well as an increased number of vision tools and enhanced communication capabilities,” he says.
For more on machine vision, visitwww.bannerengineering.com.
