In the manufacturing industry, a huge transformation is taking place—machine vision—and it is growing at astronomical proportions. This includes all types of machine vision. For instance, the market is expecting 3D machine vision to double in size during the coming six years. As of now, this technology is proving to be a vital component in many modern solutions for automation.
Several factors contribute to the increasing adoption of this technology in manufacturing. While there is greater demand for automation solutions as the industry grapples with labor shortages, the cost of automation has decreased tremendously—sensors, cameras, robotics, and processing power are now substantially cheaper—enabling greater deployment.
Technological performance has also jumped up a notch higher, and machine vision systems now have the ability to process substantial amounts of information within a fraction of a second. Finally, machine learning algorithms and advanced artificial intelligence are transforming the data collected by machine vision even more versatile, allowing manufacturers to better realize the power from those solutions. Incorporated into automation solutions, machine vision is now producing better outcomes.
The vision system of a machine is basically made up of a number of disparate parts. These include the camera, lenses, sources of lighting, robotic movements, processing computers, application-specific software, and artificial intelligence algorithms.
While the camera forms the eyes of the system, machine vision can have several types of cameras depending on the application’s needs. An automated solution may have various cameras with different configurations.
For instance, there can be static cameras, for placing in fixed positions. These usually have a more bird’s eye view of the process, useful in applications where speed is imperative. On the other hand, dynamic cameras placed on the end of robotic arms can come much closer to the process, resulting in much higher accuracy and detailed capture.
Another important aspect of the vision system is its computing power. This is the brain of the system that helps the eyes (cameras) to do their work. Computation resources, coupled with machine learning algorithms, must not be confused with traditional machine vision applications. Companies offering machine vision capability also offer software libraries for implementation.
While manufacturers design their systems specifically for application users, others offer them targeted toward software programmers. Ultimately, the software provides the machine vision system with advanced capabilities offering a dramatic impact for manufacturers. Programs are available for control of tasks along with the ability to provide feedback from the line with valuable insights.
Machine vision-guided systems are gaining steam as a concept for replacing basic human capabilities. For instance, machine vision for assembly lines enables an increasing range of processes and applications.
Typical applications of machine vision include assembly processes for power tools, medical equipment, home appliances, and industrial assembly lines. Most assembly steps in the fabrication of electronic equipment can benefit from the use of machine vision, as it offers a substantial increase in the level of precision achieved.
For instance, machine vision improves inspection of component placement of tiny surface mount components on printed circuit boards before they go for soldering. It improves the line throughput, while not succumbing to fatigue as a human inspector would.