Machine vision has slowly advanced over the last decade, particularly as more manufacturers have tapped specialist integrators with the setup of imaging on their machines. That’s because engineers in myriad industries have begun to recognize that the promises of machine vision—increased quality control and safety—are only possible when the vision system is specifically tailored to the application at hand.

Case in point:
Machine vision checks stamped parts

Stamping presses continue to be an integral part of manufacturing. Although associated processes have undergone continuous improvement, the basic nature of press operations have remained unchanged for decades … despite rising expectations for quality components from stamping machines.

In fact, penalties imposed for sending bad parts can easily reach $50,000, not to mention wasted man-hours to sort through parts returned to the manufacturer.

But defects in stamped metal components are often difficult to detect. Consider slug marks, which often only appear for only a few parts, or even just one, and then disappear after the slug embeds itself into another part and gets carried away. Another situation is when broken die pins create an abundance of wasted material, time, and missed defects during sorting.

In these and similar situations, machine vision can automatically inspect metal components as they are coming off of the press, which in turn can save money and reduce scrap — ensuring 100% quality-component delivery rate for the end user. But there are challenges to consider when applying machine vision to this task. That’s because one press can run many different parts with frequent changeovers, various sizes, inconsistent environments, and various speeds.

Understanding what vision can and cannot do for a given process within the confines of a design budget is just as important before commencing the project. These challenges are met through careful selection of camera, lighting, lens and filter. Defect size and the precision with which the machine-vision system must detect them dictate what camera resolution is suitable.

For example, in some stamping applications, a two-megapixel monochrome camera can work well. However, other applications may require higher resolution to accommodate the FOV or to adequately determine the inspection requirements within the ROI.

Also note that in most machines using a monochrome camera, the setup pairs with a red LED light with a wavelength of 625 nm or so. However, in machine-vision applications, exceptions and situational anomalies are often the norm. In one real-world application, testing showed that a white LED light with a monochrome camera made for better contrast.

In fact, due to the complex nature of imaging, only testing can confirm that a particular setup is optimized—even with nontraditional lighting and camera arrangements—for the environment and parts being inspected.

Reconsider the nontraditional setup for stamped-part inspection. Here, a diffused white LED light combined with a light red bandpass filter maximizes transmission of light in the specific spectrum between bad and good parts. High-intensity light also lets the setup inspect the parts while in motion, because camera shutter speed can be set fast enough to eliminate motion blur.

Assume vision software orients parts to within 0.001° based on a reference point as they are placed randomly on the conveyor. Once oriented, controls trigger the rest of the quality checks to determine if there are any problems with the part. If defects are found, the system can immediately stop the press or reject the parts. Or the integrator can program the machine-vision system to log details of the inspection and provide trending data.

Note that as quality requirements become more stringent so do the requirements for automatic visual inspection—but advances in hardware and software are taking vision-system capabilities to new heights.

Thank you to Skye Gorter, President of Skye Automation Inc., for this application example.

Integrated design for dimension measurement

A common problem faced with part inspection is the lack of speed with calipers, micrometers, Go and No-GO gauges, CMMs and others. This type of choke point is why engineers at Fastener Depot recently streamlined their inspection process.

Fastener Depot provides inserts and studs and fasteners from manufacturers for end-use in aerospace, defense and OEM designs. Once Fastener Depot obtains parts from a fastener manufacturer, their team reviews all the certifications and specifications. Then the team verifies the correct materials were used, counts and inspects parts for dings or foreign objects.

To boost accuracy and reduce inspection time, inspectors at Fastener Depot began using an Image Dimension Measurement (IM) System from Keyence Corp. After entering part specifications, they place a part on the IM System’s stage, press a button and measure up to 99 points in 3 sec. The system then compares the measurements to the specifications, and data are stored for reporting. What once took 10 minutes or more is now done in a few seconds.

The system uses a lens with a wide field of view and an auto-focus capability to ensure parts are always in focus, regardless of height differences.

“Before, inspectors manually measured each segment or parts dimension using micrometers and Go and No-Go gauges then compared each measurement to the drawings. With the IM system, we enter the specifications for a part into the machine and measure all dimensions in one swoop,” said Charlie Criddle, quality manager for Fastener Depot.

The IM system instantly stores specifications for each part in its database—helpful when inspecting repeat parts from the same source. Flexibility is key: “One customer may need 10% of its products inspected, while another wants every piece measured,” said Criddle. Printable reports identify minimums, maximums and averages to let manufacturers make comparisons, identify problems and easily communicate with end users.