A big road starts with small steps, and big losses start with small unforeseen breakdowns. Avoiding this and at the same time producing more helps machine vision (Machine Vision) – a technology in the concept of Industry 4.0.
Machine vision automatically captures and analyzes photographs of physical objects or phenomena. If our mothers had this device, they would set up an algorithm to analyze the head for a hat. Businesses are using machine vision more widely – to improve product quality and predict equipment accidents in the automotive, pharmaceutical, food processing industries, etc. According to analysts, the entire Machine Vision market will reach more than $ 19 billion by 2027.
The principle of operation of machine vision is quite simple (which cannot be said about its architecture). Cameras and sensors transmit images and data to the system, which it recognizes and classifies. They are then scripted to interpret. For example: if “event = overheating”, then the system performs “alert” to “worker 1”. The same scenarios can be reproduced in work with overalls or violation of the perimeter of the danger zone.
What are the benefits of machine vision?
Machine vision has become popular with equipment as companies face the following challenges:
professionals are expensive
Finding and retaining a highly qualified employee is difficult, and training new ones is time consuming and costly. Companies insure their processes by transferring part of their competencies to artificial intelligence;
people are wrong
This is typical of them: from documentation to optical illusions. When it comes to risky objects like an oil rig, it is better to exclude any dependence on the human factor;
data loves order
There are two principles in competent work with equipment data: structuredness and interpretation. For the first, people have a too chaotic system (which is the cost of pieces of paper and Excel-tables), and for the second – an arithmetically limited brain;
safety comes first
Checking the condition of equipment at high-risk facilities tickles the nerves of both workers and management. Therefore, such things are transmitted to cameras and sensors: it’s cheaper, more reliable and quieter this way.
The main advantage of machine vision is the ability (in advance or in fact) to identify anomalies. Algorithms analyze new images, compare them with previous ones, and report problems on production lines. This is useful not only for equipment, but also for products: when you need to check a large number of items on the line, machine vision is also the best solution.
Machine vision in practice
In the automotive industry, a minute of downtime can cost more than $ 20,000. Machine vision technologies like ITE’s SmartEAM or FANUC’s ZDT are helping manufacturers save on accidents, downtime and rework. These systems take photographs of cameras built into robots in a factory. Data arrays (Big Data) are sent to the cloud, where computational algorithms (Cloud Computing) analyze them and notify workers about necessary repairs. Expected results: from 70+ foreseen accidents in the first year and a half.
Another vivid example: the OptiVibe equipment vibration analysis system, patented by the Americans from RDI Technologies. Their cameras, located around the plant’s units, read equipment vibrations at 205 frames per second and transmit them to the system every fifteen seconds. Algorithms process every pixel from every image, detect vibration intensity and create a vibrogram. This allows engineers to see vibration frequency and amplitude, prevent accidents and keep equipment in good shape at all times. The result: even more efficient predictive approaches and savings in repair costs.
As you can see, Industry 4.0 tools like machine vision are an opportunity to spend less on equipment repairs and protect yourself from unplanned accidents. Over the decades in the industry, we have implemented hundreds of similar solutions from stationary systems to computing on cloud servers. If you are still at a crossroads in terms of innovation or are not sure how to invest correctly in equipment maintenance, write to our experts for a free consultation.
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