A fully automated machine consisting of mechanical, optical and software components seamlessly integrated into the assembly line. The system replaced the former human inspection of each part, automatically removing the defective parts from the assembly line. DEMO VIDEO https://youtu.be/0OjrfTAZrFA
An AI system that helps the process engineers identify anomalies in energy consumption and review energy consumption outliers for specific production lines. That leads not only to a decrease of the energy consumption, but also to prevention of machine failure incidents.
Scrap ration decreased thanks to AI prediction if the produced unit is scrap before it is fully finished. Cost reduction, time efficiency and opportunity to investigate which settings and test results lead to scraps in production.
Machine learning as a powerful tool that enables automotive component manufacturers to reduce scrap and optimize production.
Aluminium production is a complex process requiring huge amounts of electricity, so the process has to be strictly controlled and optimized to avoid any unnecessary expenses for energy and chemicals. Fortunately, machine learning can assist here.
Machine learning is a powerful tool enabling automotive component manufacturers to reduce scrap in early production stages and optimize the process. Our client decided to boost their quality control implementing cutting-edge technologies with Cognexa.
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We create AI solutions that help organizations automate processes, optimize operations and extract value from data.
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