Machine vision is a technology that is being deployed by manufacturers across every industry.
Fremont, CA: The human eye is blessed with incredible capabilities. Humans have 107 million photosensitive cells in each eye, and it can distinguish more than five hundred shades of grey, and see about three million different colors. But in the 21st-century manufacturing, even the human eye fails to provide the precision, speed, and repetition needed to facilitate quality inspections. Instead, manufacturing facilities are highly employing machine vision inspection technology for precision optical gauging. As this technology continues to progress, the global market for machine vision technology is estimated to reach nearly $15.5 billion by the end of 2022.
Vision inspection technology works by linking cameras with image processing software that is programmed to inspect the parts for dozens of criteria and confirm quality in milliseconds. Concerning speed and accuracy, automated vision inspection far surpasses human capabilities.
Machine vision technology benefits the manufacturing sector from a variety of applications, especially when it comes to inspection. A smart camera reduces the part image to a simple format, and this image is checked by quality control software to identify defects. If integrated with assembly systems, this process is a robust way to inspect, sort, and assemble products quickly.
ESI uses machine vision to inspect parts for faults and segregate them from production parts that get shipped to the customers. In one case, 40 million pins were produced annually for use in seat belts by one of the automotive customers. These pins are extremely small—less than half of an inch—so using human vision to inspect for defects is impossible. Given that these parts are critical to safety belts' function, the utmost precision and quality is needed.
This setup runs 24/7 without the requirement of a human operator. The software additionally records all finished parts, excellent and defective both, and plots them in charts to help in identifying areas for improvement in the manufacturing process.