Airlines are Increasingly Connecting Artificial Intelligence to Their MRO Strategies
Predictive maintenance is still in its infancy for commercial airlines, but in the future will evolve into intelligent maintenance for large-fleet commercial operators.
Predictive maintenance is still in its infancy for commercial airlines, but in the future, predictive will evolve into intelligent maintenance for large-fleet commercial operators.
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.
A challenge exists for airline maintenance teams dealing with the large amount of data being produced by newer generation aircraft: the need for an intelligent application, bot or computer program capable of generating a specific work order task for maintenance technicians, rather than large volumes of data that they have to aggregate and analyze to produce an actionable result. In some cases, an action isn’t even taken, and a technician or engineer simply discovers a no-fault found situation.
Right now, Delta Air Lines is working on adopting artificial intelligence and machine learning into its aircraft maintenance strategy. James Jackson, Delta Air Lines manager of predictive technology engineering, provided a look at how airlines are approaching the use of artificial intelligence within their maintenance strategies during an “intelligent maintenance” themed presentation at the 2019 AEEC/AMC and MMC general session.
“We want to integrate some of the more advanced technologies such as machine learning, artificial intelligence, natural language processing and deep learning into our predictive maintenance process. With the increased digitalization of data, we want to have our technical airplane specialists focusing more on validation rather than the aggregation and analysis of maintenance data,” said Jackson.
While Delta is not the only airline thinking about the use of artificial intelligence for maintenance, Jackson’s approach to the use of AI shows how it can be an effective tool for airline mechanics well into the future. Jackson’s presentation focused on the use of artificial intelligence primarily to replace today’s human tasks of ingesting, aggregating and analyzing raw data transmitted by aircraft.
Instead, Jackson wants to use artificial intelligence to generate an accurate work order straight from the analysis of the data.
“If I have an alert that is a single failure mode, then why can’t I automate that and have the alert trigger out prescriptive instruction in our [maintenance information system], to send those out to maintenance to include the parts, tooling, the routing of the aircraft. That way, we have our experts focused on responding to alerts that include instances where their specialized skills are needed, rather than a single failure alert,” said Jackson.
Jackson also explained how one of the primary reasons why Delta wants to adopt an intelligent maintenance strategy is a result of not only the amount of aircraft that the airline has within its fleet, but also the variety of their aircraft models as well. This is also a reflection of how and why the broader commercial airline industry is adopting AI as a decision tool for aircraft maintenance.
Delta’s global fleet, according to its annual report filed February 15, 2019, stands at well over 1,000 aircraft between their mainline and regional brands. According to Jackson, at peak operations the airline operates 3,500 flights per day. Their maintenance team is responsible for 23 individual aircraft types and 25 different engine models.
