We at produce different computer vision technologies. In this blog we tell about using machine vision in production for some common use-cases. TaQadam What Machine Vision is and where it is used Machine vision is a technology in the field of artificial intelligence for . In general, the tasks of machine vision systems include the capture of the images on the device, processing , and link it to machine response. image recognition on the edge Computer or machine vision technologies are used across different industries: from traffic control and public services, medical imagery, and robotic processing at industrial sites. As penetrates across our lives, there is an increasing interest in for optimizing the manufacturing production. Today, machine vision systems are an for controlling performance, detecting anomalies, and reducing human supervision at site. Industrial 4.0 revolution machine vision AI, IOT (internet of things) effective tool Use cases: automating production Sensors and industrial cameras have opened up in the of the production process new perspectives automation : measurement (measuring/testing specific product dimensions) (checking the correct position of all parts on the assembly) product verification (barcode and 2D code reading, product type determination based on shape, size, and other characteristics) product identification (for example, sorting packages by color, etc.) product sorting (determining the position of the product on the assembly line and using its coordinates for IOT device). navigation system Use case from: Blumenbecker group Use cases: safety and protection​ In the field of industrial safety, there are several important tasks. Perimeter control as a measure against crime and unlawful trespassing . These video analytics has been around for years. But with computer vision AI, there is a likelier chances it to be detected early. Safety movement control. In the companies of chemical or metal production, the departments of Hazardous Materials Safety, has been implementing the monitoring systems using AI. With the better control, there is a reduced risk of employees to avoid injuries, in loading or uploading or approaching certain areas. In some advanced cases, sites are using historical video analytics to design the paths for optimized and safe performance at production. Another example of a safety-related application is detecting helmets or safety gear . Computer vision and machine learning have made it possible to automatically identify non-compliance. All these techniques lead us to the case, where AI will also bring a significant data value to insurance companies. What is more, it can become easier to solve insurance cases. Use cases: quality control Machine vision in production can also be used for quality control. This task can be divided into . two components One is related to . You can view the dimensions of certain objects. Most often, this concerns small things: some caps from milk bags or bottles. They have a fairly simple cheap production process, a lot of defects, they just need to be filtered out, it is not profitable to make details better. physical quality control The second task is to determine . Using the video camera, you can automatically see what events are happening, and track the correctness of the employee’s actions, as well as monitor the speed of work. whether the actions are performed correctly Use cases: anomaly detection Machines are humans often when it comes to repetitive work. replacing An who spends hours at work analyzing the defective parts, for example, is prone to . This is the situation in which machine vision is essential to increase the overall performance. Computer vision based on machine learning can and anomalies at the infinitely larger number. engineer make more mistakes automatically detect defects Sensors scan all the details and send a signal if something is wrong. Cameras paired with LEDs carefully study the image and transmit the images to the computer. It already has a large database trained on anomalies recognized in the past, and it will instantly give the command to the operator further down the pipeline to sort them out. Our work at industrial Machine Vision ​ Helmets detection ​ Details detection Forklifts detection Machine vision allows to (the system performs the operations that people used to do, works without interruption) and simultaneously performed, which, in turn, itself. Using machine vision allows to track the quality of items that have a complex shape, large or very small area. In general, investing in the creation of a machine vision system should be considered as the first step towards high-tech production. reduce the cost of production improve the quality of the operations improves the quality of the product Originally published at: https://taqadam.io/machine-vision-in-productio

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Machine Vision Technology in Production: Use Cases

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