Hoselton identified this application as a good one for machine vision. “We have long used machine vision in this plant because of our intense focus on quality,” Hoselton said. “In fact, we have systems from all three of the leading suppliers of machine vision systems. For this project, we selected the Cognex In-Sight? vision system because it is so easy and fast to program. I went to a Cognex training class and in only ten minutes developed a simple application that reads a business card. Based on that experience, I programmed this application in only about 45 minutes including interfacing the vision system to the assembly machine’s programmable logic controller (PLC) and human machine interface (HMI). There was no need to get internal engineering resources or an integrator involved.”

Hoselton selected an In-Sight 5000 Series vision system because it provided a complete solution in a modular package and did not require any additional hardware or other equipment. The 60mm x 110mm x 80mm package of the vision system easily fits within the tight confines of the manufacturing plant. The In-Sight 5000 Series model selected offered a resolution of 1600 x 1200 pixels and an image acquisition time of 15 frames per second. Cognex EasyBuilder? software walks the user step-by-step through the process of setting up a vision application. Users can drop in tools simply by clicking on features of interest.

Programming the vision system

Hoselton began the programming process by mounting the vision system on the assembly machine and connecting it to the PLC, HMI and a laptop computer running the EasyBuilder software. He pointed the vision system at a part and the resulting image appeared in the EasyBuilder interface on his laptop. He used a wizard provided by the software to set up the scale and nonlinear calibrations. He selected edge tools to identify the location of each side of the housing based on the transition from the black part to the white background. He used additional edge tools to identify each side of the opening in the part where the retainer is inserted, again based on the transition from black to white. Hoselton then used measurement tools to calculate the size of the opening by subtracting the lengths of the walls of the housing from its total length. He plugged the tolerances into the measurement tools from the blueprint. Based on these tolerances, the vision system measures the gap and sends an alert when it varies by an amount as small as 0.1 mm.

Hoselton used the point-and-click communications setup in EasyBuilder to use a signal from the PLC to alert the vision system to acquire an image when a new part is in position. He sent the results of the inspection back to the PLC and the HMI. Finally, he used additional tools to set up a user interface that shows the image of the latest part, a filmstrip that shows recent parts, and a table of results. The vision system inspects each part in only about 40 milliseconds, much faster than required strokes-per-minute production rate of the machine. The HMI used by the operator of the assembly machine is connected to the plant network so JST managers can now see the images from the machine vision system from their desks, either in real time or by searching archives.

Improving already high levels of quality

The In-Sight vision system has provided a significant improvement in the company’s already high quality levels. Manufacturing personnel receive immediate feedback from the vision system for even tiny variations, which are far too small to affect performance and too small to be seen with the naked eye. The assembly machine operator immediately gathers up the parts along with the inspection information and takes them to the quality control department. Quality control takes the parts to the molding technician where he immediately begins working to address the issue. As a result, the time required to determine the root cause of and address manufacturing variation has been reduced to one day. The cost of a nonconformance report has been reduced from $1,500 to $100.

Most important, the ability to detect and correct even the smallest variations has resulted in the company exceeding demanding six sigma quality objectives. In the most recent measurement period, there was not a single defect in several million parts produced by the company. JST managers attribute this to the implementation of the machine vision system. “Quality is by far the most important factor in our company’s success,” Hoselton concluded. “Machine vision has helped us make significant improvements by helping us detect variation faster so we can make corrections before defects occur.” Based on the success of this application, Hoselton set up another In-Sight vision system on a similar assembly machine that produces a different product. The main difference between the two products is that the gap in the housing is a different size. Hoselton started with the program that he developed for the first assembly machine. In only 15 minutes, he was able to tweak the original program for the new product.