Published:14.11.2024
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CSG Aerospace has developed the AI-powered system JATISmro to streamline aircraft repairs

The development of JATISmro is the result of synergies between CS Soft and Job Air Technic, both part of the CSG Aerospace division within the CSG industrial and technology group. Early data and experience suggest that it enables aircraft maintenance facilities to increase efficiency by up to ten percent, translating into savings worth millions.

CS Soft, in collaboration with aircraft maintenance company Job Air Technic, has developed the JATISmro system, which significantly enhances the efficiency of all processes involved in the servicing and repairing of commercial aircraft. The system leverages models based on artificial intelligence and machine learning, utilising historical data.

Using this data, JATISmro can predict potential maintenance tasks, material and tool requirements, and allocate human resources, thereby streamlining the entire aircraft maintenance process. The system has been operational at Job Air Technic for several months and will now be actively offered to other customers by both companies.

The development of JATISmro is the result of synergies between two companies that are part of the CSG Aerospace division of the CSG industrial and technology group. Job Air Technic is one of Europe's largest companies specialising in aircraft maintenance and repair (MRO). CS Soft primarily develops air traffic control software, but it also has a team of specialists focused on creating AI-powered software.

“We worked closely with Job Air Technic to develop JATISmro over approximately three years. It has been in use at the company for over a year now, and early data and experience suggest it enables aircraft maintenance facilities to increase efficiency by up to ten percent. While we don’t yet have a detailed calculation, even a few percentage points translate into savings worth millions,” explained Lukáš Hefka, Head of AI at CS Soft.

“The system is also continuously improving through feedback learning, as the models are automatically trained on current real-world data every week,” Hefka added.

Source: https://www.byznysnoviny.cz/
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