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Machine vision is an image-processing technology that enables automated object scanning within a set field of view. In industry, machine vision is being incorporated to further develop industrial processes, identify areas of improvement and enable intelligent locomotion within robotics. Plant operators can mount cameras on production lines or cells for real-time process control, product inspection and sorting, and robot guidance.
The technology enables robots to interpret their visual surroundings, which can allow them to move around independently. Visual information can be used to recognize the environment and make decisions that are not directly programmed.
A camera does not see in the same way as the human eye. Machine vision systems use pattern detection software to examine data and draw conclusions based on prior knowledge. This technique is particularly useful when inspecting the quality of raw materials and final products for component flaws or defects. For example, if a problem is found, a part can be redirected or the process corrected to resolve the issue.
In addition to flaw detection, machine vision can be used to ensure operations are traceable using identification tags. A camera can read the tags, allowing the information to be used to direct the product or to chronicle which stage certain parts are in the supply chain.
Smart cameras and sensors can digitalize and transfer information, decoding what they capture and removing the need for human interpretation. The machine can then decide whether the information should be communicated to a central control system. These low-cost, easy-to-use systems often are a good option for those looking to streamline automated manufacturing.
Machine vision is central to the idea of the smart factory, which is based on a self-organized system consisting of a communication network and an intelligent exchange of information. Acting as the eyes of the factory, image-processing systems can compute information that was previously obtained by manual testing. This reduces human error and enables robots to react flexibly to information for production control.
Because image-processing equipment captures, gathers and exchanges data, it is a key technology for interconnected production processes. This data not only can be transmitted to the value chain but also used to trigger intelligent actions.
The technology can even be utilized to examine the state of production machines for wear and tear. This information is useful for maintenance and can alert a plant manager of the need to order a replacement component before it breaks.
As machine vision systems decrease in size and increase in speed, accuracy and resolution, their popularity is only expected to grow over the next few years, helping you see the way to the factory of the future.
Jonathan Wilkins is the marketing director at EU Automation, an obsolete industrial parts supplier.