Machine vision is the vision of a machine; in other words, it is to endow a machine with visual perception, enabling it to have scene perception capabilities similar to those of biological visual systems.
What are the applications of machine vision?
Abroad, machine vision is primarily used in the semiconductor and electronics industries, with the semiconductor industry accounting for 40% to 50% of applications. Examples include PCB printed circuits, SMT surface mount technology (SMT), and electronic manufacturing equipment. Furthermore, machine vision has wide applications in various aspects of quality inspection and other fields.
The main task of machine vision is to generate a set of descriptive information about the scene or objects involved in the image by analyzing the image.
In other words, the input to a machine vision system is an image (or a sequence of images), and the output is a perceptual description of these images. This description is closely related to the objects or scenes in these images, and it can help the machine complete specific subsequent tasks, guiding the robotic system to interact with its surrounding environment.
Six common applications of machine vision in manufacturing
1. Printed Circuit Board Production: In equipment such as exposure machines, SPI, and punching machines, machine vision positioning and inspection technologies can achieve rapid and accurate quality inspection and process control, improve product quality and production efficiency, and are a reliable guarantee for improving equipment performance.
2. Electronic product manufacturing: From upstream ITO glass coating, photolithography, 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 inspection, higher requirements have been put forward in the process, making machine vision technology an essential technology in production and quality inspection.
3. Application of surface mount technology: By using machine vision positioning, measurement and inspection technology, the production efficiency of SMT equipment can be improved, the placement accuracy can be improved and the stability of continuous operation can be improved, which will help upgrade the equipment in the SMT industry.
4. Applications in Industrial Robots: Machine vision is used in intelligent industrial robots in the industrial field. Multi-joint manipulators or multi-degree-of-freedom robots replace manual labor in industrial production, performing monotonous, frequent, and long-term operations, or operating in dangerous or hazardous environments.
5. Pharmaceutical manufacturing: Machine vision can be used to achieve quality control and management control of the pharmaceutical manufacturing process.
6. Product quality inspection: Machine vision can inspect products based on their surface quality characteristics, such as dents, scratches, cracks, wear, surface precision, roughness, and texture.
What are the prospects for the development of machine vision in China?
my country's machine vision industry started much later than many developed countries, around the 1990s. Initially, it mainly focused on acting as an agent for foreign machine vision products. It wasn't until the 21st century that a few domestic machine vision companies began to develop their own products.
According to CBInsights data, China is currently the third largest market for machine vision applications after the United States and Japan. Including machine vision equipment, the localization rate is about 40%, and it is expected to increase to 55% by 2022.
Currently, the machine vision industry is in a phase of rapid growth. Since 2020, the global market size of the machine vision industry has exceeded US$10 billion. However, while the scale of China's machine vision industry is still relatively small, its growth rate is fast and its development is considerable.
Machine vision has evolved far beyond a standalone application. Machine vision hardware and software products have become essential components in all stages of manufacturing, placing higher demands on system integration. Industrial automation companies require integrated industrial automation systems that can work collaboratively with test or control systems, rather than standalone vision applications.
