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Machine vision systems deserve a second look from automotive manufacturers
Machine vision systems deserve a second look from automotive manufacturers
25-03-27
With the development of technology, people's demand for the interactive experience of electronic products is getting higher and higher. Touch screens, as a new generation of electronic product input devices, are gradually becoming the new favorites for tablets, mobile phones, e-books, GPS, game consoles, and other devices. The production process of touch screens is complex, from upstream ITO glass coating, lithography, and IC component processing, to midstream touch screen module bonding, screen printing, and cutting, and then to downstream touch screen module bonding and cover glass detection, all of which have put forward higher requirements in terms of technology, making machine vision technology an essential technology for production and quality inspection related links.
Visual sensors are the direct source of the operation of the entire machine vision system. Each whole mainly consists of one or two graphic sensors, in addition to which it also needs to be equipped with a light projector and other equipment for cooperation. The main function of the visual sensor is to obtain the most original image that the machine vision system needs to process. Image sensors can use laser scanners, linear and area array CCD cameras or TV cameras, or the latest digital cameras.
Visual sensors must have the ability to capture a large number of light rays and point array pixels from a whole image. The clarity and fineness of the image are usually measured by resolution. This ability is usually reflected by the number of captured pixels. Some companies' sensors can capture 1.3 million pixels, so sensors can capture a large number of clear images to convert into data for operation, regardless of the distance.
Visual sensors are relatively low in cost and are currently being used in large quantities. They are widely used in embedded MCUs or robots and safety inspections. Many products have high reliability and do not even need pre-testing to be used, which proves that visual sensors have high compatibility and versatility.
Machine vision also has corresponding learning capabilities, combined with AI Large models for cloud learning or local learning, so the efficiency of detection or production can be improved during continuous work.
Machine vision has many applications in the industrial field. First, it improves production efficiency. Machine vision technology can automatically detect, classify, and identify products on the production line, thereby reducing manual intervention and error rates. At the same time, through real-time data analysis and predictive maintenance, the reliability and maintenance efficiency of equipment can be improved, and downtime can be reduced.
Secondly, it can improve product quality. Machine vision technology can perform high-precision detection and identification of products, thereby ensuring product quality and consistency. Through machine vision technology, rapid feedback and adjustment on automated production lines can be achieved, problems can be found and solved in time, and product quality and customer satisfaction can be improved.
Cost is a factor that factories need to consider during production. As mentioned above, visual sensors are relatively low in cost, so machine vision technology can reduce production costs and waste of human resources. Through automated and intelligent production methods, manual intervention and error rates can be reduced, the rate of defective products and waste products can be lowered, the utilization rate of materials and energy efficiency can be improved, thereby achieving cost optimization and sustainable production.
The widespread application of machine vision technology in manufacturing has made it one of the important means to promote the all-round intelligence of manufacturing. In many fields such as automobile manufacturing, electronics manufacturing, and medical device manufacturing, machine vision technology has become the standard configuration of intelligent manufacturing.
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