Inside Machines: Pinpoint Inspection Precision via Machine Vision
An electronics components manufacturer uses machine vision to achieve 100% inspection of interconnect pins, improving quality control and eliminating costly product returns.
Machine vision is helping Bead Industries, an interconnect pin manufacturer in Milford, CT, improve collaborated several years ago with a large automotive electronic manufacturing services (EMS) company in the Midwest to develop a high-performance interconnect pin for use in automotive actuator control systems. The result was Bead's patent-pending "True Grip" Tandem Pin with a unique flanged design that provides superior rigidity, alignment and electrical conductivity while requiring less solder.
Ensuring that each of the tens of millions of pins produced on several machines precisely met all specifications presented a considerable challenge. Each pin has only a 0.040 in. diameter and 0.472-in. length. Manual inspection at periodic intervals was effective, but impractical as volume requirements increased.
Although Bead's customer did not require 100% inspection, “an in-process, high-speed vision inspection system that could measure multiple dimensions on every pin and store the data was the only way to achieve total confidence in our process and product,” says Kevin Mayer, Bead Electronics plant manager. Bead Electronics manufactures precision continuous reeled, solid-wire, and tubular contact pins for the telecom, automotive, connector and lighting industries.
Producing 350 ppm
In fall 2008, Bead engineers began researching automated vision inspection systems to verify the diameter, thickness and length of the flange, and to measure the overall length of each pin as it came out of the die-set. Mayer ultimately chose VA61 Vision Appliances, Genie cameras and Sherlock software from Dalsa. With the presses running at 350 parts per minute (ppm), no other type of inspection solution could keep pace reliably, he says. “The Sherlock software [also] was more user-friendly than any of the other programs we looked at,” he adds.
Dalsa's IPD VA61 compact vision controller connected to Genie gigabit Ethernet cameras were installed on each of the three production machines. Sherlock software running on the vision controllers allows operators to get the system up and running quickly with the simple click of an icon. The software's tool suite enables Bead to obtain precise quality control measurements and identify trends that could lead to non-conformances.
Mayer says that because the software “is flexible and easy to use, we program our vision inspection stations for other components and other machines on our plant floor as our production schedule requires.”
Each vision inspection station is networked to Bead’s database. The inspection data collected provides traceability down to the day, hour and minute of production. This allows analysis of raw dimensional data, and provides insight into process variables such as tool wear.
By analyzing production trends, Bead is able to predict tool life and proactively schedule tool changes and other preventive maintenance. “This has improved our efficiency tremendously, since we can prepare for and schedule tool changes rather than having to react to a potentially catastrophic tool failure,” says Mayer.
Since installing the Dalsa machine vision systems late in 2008, Bead has achieved 100% inspection of each of more than 50 million pins produced, and the company has experienced no costly product returns.
“Because of these machine vision systems, Bead Industries and our customers have complete confidence in every single pin produced,” Mayer says. “Our goal is to have a vision system on every machine in our plant so that we can provide 100% inspection for all of our products. ”
Fernando Serra is Eastern regional sales manager for Dalsa Industrial Products, Billerica, MA. For more than 25 years Dalsa has designed, manufactured and deployed digital imaging components for machine vision applications, including automated inspection, test and measurement. Edited by Renee Robbins Bassett, firstname.lastname@example.org.
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