Machine vision, sometimes called computer vision, is the ability of a computer system to analyze and process visual information. Once the visual information is processed, any machine or software system can then act on it. Both hardware and software components drive this process.
Machine vision relies on artificial intelligence (AI) to analyze visual information. By giving our machines “eyes,” machine vision can accomplish incredible tasks such as alerting us to system failures or hitting the vehicle brakes to avoid accidents.
While the term “machine vision” may sound futuristic, it’s more commonplace than we may think.
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Machine Vision: The ‘Eyes’ of Industrial Equipment
When researching machine vision, we find that its most common use case is within industrial environments. For example, machine vision is typically used for processes such as visual inspection. In many cases, a machine will perform routine inspection tasks on itself. If there are existing issues within the machine’s components, it will send an alert or perform another action.
The use of machine vision in industrial settings is growing rapidly. According to market data, the global machine vision market was valued at $13.23 billion in 2021. The market is expected to grow at a CAGR of 7.7% between now and 2030.
According to the above market report, the demand for quality inspection and automation within the industrial sector will drive machine vision growth and adoption.
How Machine Vision Works
Machine vision requires the use of both hardware and software components. Some examples of hardware include lights, cameras, specialized lenses, and sensors. The hardware is responsible for image capture.
Software components may include processing software and algorithms. These AI and ML components are responsible for processing the images into a format the machine can understand.
The machine vision process will differ depending on factors such as the type of machine and its function. To illustrate how the process works, let’s consider a simple manufacturing example.
An Example Machine Vision Process
Let’s say that a manufacturing plant wants to perform a routine inspection using machine vision. First, a camera will capture an image of a machine or its components. That image will then be translated into a digital format.
The accompanying software will then analyze the image using algorithms and predefined rules. In this example, the software would look for machine defects or signs of potential failure.
After the analysis is complete, the machine will take a specific action. For example, the machine may shut down to avoid further defects if issues are found. Or, the machine will continue its work if it passes inspection.
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Machine Vision Use Cases
When it comes to manufacturing specifically, there are an endless number of use cases for machine vision. For example, machine vision can be used for processes such as predictive maintenance, where machines use visual information to predict future maintenance needs. As a result, machines receive the maintenance they need before failures occur.
Another example within manufacturing is product inspection. Machine vision can be used to capture visual information about products as they progress on the line. If defects are found in the products, they can be removed from the line, improving product quality and saving resources.
Machine vision’s use cases don’t stop with industrial manufacturing. In fact, every industry can benefit from machine vision, which is often referred to as computer vision when used outside of the industrial sector (more on this below).
For example, computer vision is a key component in self-driving vehicles. Hardware and software enable a car to “see” its external surroundings, such as stop signs and other vehicles. After the analysis of the visuals, the car will act autonomously.
Computer vision is also becoming prevalent within the healthcare space. For example, computer vision has been tested as a promising tool for the diagnosis of COVID-19. Other developments in healthcare include computer vision processes for finding cancer and intelligent health monitoring.
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The Various Benefits of Machine Vision
There are many key benefits we can experience from allowing our machines to see. For example, machine vision can improve product quality in manufacturing and reduce costs across industries. Because machine vision is still gaining mainstream adoption, there are other benefits we have yet to discover.
The manufacturing industry faces many challenges. And one of the most costly is unplanned downtime. According to recent data, unplanned downtime costs industrial manufacturers an estimated $50 billion annually. That same data states that equipment failure causes a whopping 42% of this unplanned downtime.
Many manufacturers have looked to technology for help. Machine vision can prevent downtime by enabling machines to foresee equipment failure before it occurs. As a result, downtime can be planned and repairs made with little to no effect on the enterprise.
Identifies Safety Risks
According to the CDC, one of the leading causes of work-related injuries is contact with objects and equipment. Some of the injuries are directly caused by machine component failure.
To prevent workplace injuries, enterprises must do what it takes to ensure equipment is safe to use. Machine vision can help identify safety risks that may go unnoticed by human inspection. And through processes such as preventative analytics, these safety risks can often be identified and mitigated before they result in injury.
Identifying safety risks isn’t just for the manufacturing industry. For example, through computer vision, self-driving cars can identify safety risks in real-time, stopping short of an accident or obeying road signs.
Improves Product Quality
It’s no secret that most products we purchase are mass-produced, from the vehicles we drive to some of the food products we consume. When it comes to the safety and well-being of consumers, product quality is a top priority for all manufacturers.
Unfortunately, manual inspection processes take serious time and resources. Machine vision can support manual inspection processes through automation. Using cameras and computer algorithms, products can undergo inspection for defects before they ever leave production.
As discussed above, manufacturers can reduce unplanned downtime, potentially saving thousands or millions each year. However, cost reduction when using machine vision doesn’t stop there.
For example, machine vision can reduce equipment costs. By improving routine maintenance processes through machine vision, manufacturers can boost equipment performance and ensure the expensive components stand the test of time.
Machine Vision vs. Computer Vision
Machine vision and computer vision are two terms that are often used interchangeably. And while they are very similar and related, there is a key difference.
Computer vision is most often used as the umbrella term for the basic process of capturing and analyzing visual information. Machine vision, on the other hand, is typically used to describe specific industrial use cases where heavy machinery is used. In other words, machine vision can be viewed as a subset of computer vision.
The Future of Machine Vision
Technological advancements will continue to improve machine vision and open the door for more opportunities. For example, edge computing will soon allow the machine vision process to occur at the source of the data, resulting in real-time action. We can also expect machine and computer vision to become prevalent in other industries, such as retail and agriculture.
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