Artificial Intelligence for Airline MX needs to include FAA’s SMS

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Connections to airplane part status useful for MX and SMS

Artificial Intelligence should include this Safety Data Resource

FOQA major contributor to Recent Reduction in Aviation Safety Risks

Airlines are Increasingly Connecting Artificial Intelligence to Their MRO Strategies

The use of artificial intelligence (AI) is expanding as a decision-making tool for airline maintenance teams at large fleet commercial airlines.

Airlines based in the U.S., Europe and Asia have been quietly adopting AI tools in the form of intelligent agents for data modeling and simulation to the use of cognitive computing. The use of AI within airline maintenance strategies is evolving into an advanced and expanded use of predictive data analytics.


On the aircraft manufacturing side of commercial aviation, Airbus has also emerged as an industry leader actively looking to introduce the increased use of artificial intelligence into airline maintenance operations. Airbus has already established Skywise as its official predictive maintenance and advanced data analytics platform. It serves as a singular access point to data analytics that combine multiple sources into one secure cloud-based platform, including work orders, spares consumption, components data, aircraft/fleet configuration, onboard sensor data and flight schedules.

EmbraerX presents Beacon, a business platform to streamline the aviation services ecosystem

This innovative platform is designed to connect and synchronize industry resources, the aftermarket supply chain, and aviation services professionals in a more agile and efficient way, to keep aircraft flying.

Thai Airways Is Investing Millions in Predictive Maintenance, MRO Service ExpansionThai Airways, under a new partnership with Airbus and backed by Thailand’s Board of Investment, is investing in the use of drones, robots and predictive maintenance technologies for the creation of a new maintenance, repair and overhaul hub at U-Tapao Airport to capture future increased demand for aircraft services that will result from the ongoing growth of the Asia Pacific commercial airline fleet.

7 Ways Airlines Use Artificial Intelligence and Data Science to Improve Operations

Only one of 7 and safety only in the title

2. Air safety and airplane maintenance

Airlines literally bear high costs due to delays and cancellations that includes expenses on maintenance and compensations to travelers stuck in airports. With nearly 30 percent of the total delay time caused by unplanned maintenance, predictive analytics applied to fleet technical support is a reasonable solution.

Carriers deploy predictive maintenance solutions to better manage data from aircraft health monitoring sensors. Usually, these systems are compatible with both desktop and mobile devices, granting technicians access to real-time and historical data from any location. Knowing an aircraft’s current technical condition through alerts, notifications, and reports, employees can spot issues pointing at possible malfunction and replace parts proactively. Executives and team leads, in turn, can receive updates on maintenance operations, get data on tool and part inventory, and expenses via dashboards.

With applied predictive maintenance, an airline can reduce expenses connected with expedited transportation of parts, overtime compensation for crews, and unplanned maintenance. If a technical problem did occur, maintenance teams could react to it faster with workflow organization software.

The essential brilliance of Artificial Intelligence is the system of connectivity—the gathering of information for processing and analysis that contributes to knowledge. The above five articles describe how AI is being utilized by airlines. There are many, many more which discuss how this use of data and computers are being used to improve customer experience, revenues, load factors and the like.

These articles all include how the AI systems help improve maintenance quality, costs, predictability of repairs/maintenance, spare parts, inventory integrity and operational considerations. Only one of the reports mentions SAFETY and that reference is only in the introduction. Focus on the hard numbers attributed to the MX cost center is understandable for a P&L institution.

What is unfortunate is that a major source of global aviation safety improvement is the collection of data from multiple sources

  • ASRS (voluntary submission of data by crews),
  • ASIAS (the hub which integrates the numbers and distributes),
  • CAST (a collaborative effort to identify and respond to risks),
  • VDRP( a voluntary reporting system that contributes incidents)


  • FOQA (a system linking data from aircraft).








Finally, all of this safety relevant (which includes maintenance relevant) information is the crux of the FAA’s and world’s aviation regulatory authorities Safety Management System. Plus, these systems are being replicated on a global basis—GSIP.










AI has even greater value for these safety uses. The absence of reference in the articles does not mean that these MX information systems are not/ cannot include links to the SMS network. Hopefully the architecture is not so mature that it cannot be modified to transfer this important information. If it is not possible that would be unfortunate.


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