Machine vision is a technology that combines hardware and software that offers operational guidance to devices by capturing and processing images.
Machine vision system technology involves a machine using cameras and artificial intelligence (AI) algorithms to identify, detect, and verify images to create a defined output. Machine vision can execute specific outputs because the AI algorithm makes the system understand its captured images.
While not as advanced as human sight, computer vision has advanced to the point that it’s critical for businesses today, especially those in the manufacturing industry. As a result, companies are setting aside a budget for this technology that helps electronic devices to recognize images like a human, without the variable of human error.
The Importance of Machine Vision
While the human eye is excellent for qualitative analysis, machine vision is critical in providing quantitative measurements because of its speed, repeatability, and accuracy. The technology helps companies by:
- Improving quality in inspection, gauging, measurement, and assembly verification
- Improving productivity by executing a repetitive task that a company manually does
- Enhancing production flexibility
- Lowering capital equipment costs by improving machine performance
- Reducing production costs by detecting flaws early in the process
Manufacturing companies can use machine vision to execute a variety of functions, such as:
- Presence detection
- Digital statistics
- Defective product detection
- Identification, such as code reading and color recognition
However, you shouldn’t confuse machine vision and computer vision. While machine vision systems use cameras to view images, computer vision uses AI algorithms to interpret the image before instructing other components in the system to work on the information.
How Does Industrial Machine Vision Work?
To understand how industrial machine vision works, you need to examine its basic components, which include the following:
- Lighting: Lighting in machine vision illuminates the target. Lighting involves a light source and its placement with respect to the part of the camera.
- Machine vision cameras: Cameras used in machine vision have sensors that convert light from the lens into electrical signals for the machine vision system that captures pictures for inspection.
- Vision processing unit: The processing unit consists of AI algorithms that determine the basic geometry of images that the camera captures and make decisions depending on image characteristics.
- Communication: The vision system uses a variety of off-shelf components that must co-ordinate to connect the machine vision system
These parts of machine vision work together to provide exceptional automated visual inspection processes such as accurate positioning, measurement, and defect detection.
Primary Types of Machine Vision Solutions
Your business can utilize three main types of machine vision solutions, which include:
- 1D system: A 1D system analyzes a digital signal one line at a time instead of examining the entire picture simultaneously.
- 2D system: In a 2D system, the camera executes an area scan that captures 2D images.
- 3D system: A 3D system includes multiple cameras or one or several laser displacement sensors that examine the entire picture of the target.
Machine Vision Market Projections
According to Allied Market Research, the market value of machine vision in 2021 was $13.23 billion and might hit $74.9 billion by 2027. With machine vision, businesses can automatically analyze and inspect the production line by capturing images in process control, verification, robotic guidance, measurement, and other functions.
Machine vision also promises benefits such as reduced reliance on manual labor, easier training, and minimized human error, which streamlines workflow and increases profitability. This, in combination with an increasing demand for quality inspection and automation, will likely drive market success in the coming years.
Conclusion
In summary, machine vision involves using deep learning and neural networks to help replicate human vision for production applications such as positioning, measurement and defect detection. Recent advancements promise to diversify the use of machine vision over the coming years, giving this technology a bright and profitable future.
At Maxcess, we offer vision system solutions that ensure consistent, reliable, and automated control. Contact us today for technology that automates your processes.