Lockheed Martin, collaborating with SAS Industries, is utilizing machine learning and AI to transform aircraft MRO and optimize performance, ensuring the readiness of the C-130J Super Hercules for future missions.
Lockheed Martin, collaborating with SAS Industries, is utilizing machine learning and artificial intelligence (AI) to transform aircraft maintenance and optimize performance, ensuring the readiness of the C-130J Super Hercules for future missions.
A specialized team has created HercFusion, a suite of tools utilizing data from nearly 3 million C-130J flight hours to forecast part replacement requirements, thereby ensuring the continuous operation of fleets worldwide in support of various missions.
HercFusion provides machine-learning insights to C-130J operators, empowering maintenance crews with optimized strategies for aircraft upkeep, leading to:
– Enhanced aircraft availability
– Improved mission readiness
– Long-term cost savings
Mike Isbill, Lockheed Martin Technical Fellow specialized in Digital Sustainment Analytics said, “HercFusion allows the maintenance ops team and the flight ops team to look at the health of an aircraft, down to the part level, and determine the best aircraft to deploy. That way, users can schedule when they do their maintenance while they have all the parts and support equipment in place to do that [maintenance].”
HercFusion introduces 5th generation sustainment capabilities, enabling operators to transition from unscheduled to scheduled maintenance practices.
Every C-130J Super Hercules is equipped with 600 sensors, collectively generating 3GB of data per flight hour. HercFusion meticulously analyzes this extensive dataset, employing advanced algorithms to forecast part replacement requirements. This proactive approach allows maintenance teams to strategically position spare parts, ensuring uninterrupted aircraft operation. Customers can more effectively plan for deployments with the help of this information.
Mike Isbill said, “It lets operators know what they need to take in their pack-up kits, because they know the health of that aircraft when they get ready to deploy.”
The implementation of this predictive maintenance model demonstrates a notable 3% rise in mission capability rate.
“That may seem like a small number but it actually can represent having a completely extra aircraft in your fleet, It’s huge cost savings, it’s an aircraft they didn’t have to buy, it’s parts they don’t have to buy. We’re getting more up-time for the customer, at lower cost to them and a safer aircraft for the crew.”, said Isbill.
One HercFusion operator experienced a substantial 15% decrease in fuel consumption.
Isbill said, “We’re able to reduce some of their maintenance time, and they’ve actually seen about a 15% reduction in fuel usage, so a cost savings, saving to the environment, and the goal is to continue to improve that mission capable rate. The less time the aircraft is down having to do maintenance — especially if it’s troubleshooting you really don’t need to do because our AI can tell you don’t need to do it — is a huge benefit.”
What Comes Next
In an ever-evolving battlespace, the team continues to leverage AI technology to aid customers in completing missions with increased speed, accuracy, and safety. Currently, the team is striving to integrate machine learning and AI tools onto aircraft, aiming to enhance onboard capabilities.
- As aircraft depart, operators will carry the tool with them, enabling them to feed data back to the base through 5g.mil. This data can then be reviewed by base maintainers in nearly real-time, facilitating prompt analysis and decision-making.
- “You’re not going to have bases in permanent places; you’re going to have bases that have to move. You have to be able to know where the parts need to be, when [the parts] need to be there, and then get [the parts] on and out as quickly as possible,” stated by Isbill.
Through modifications to the data and operational settings, these algorithms are versatile enough to suit various aircraft models. The team’s broader goal is to extend the use of this machine learning and AI technology to additional platforms and products.
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Isbill said, “Every day we move forward, we create new algorithms, we create improvements to the algorithms we have. We get closer and closer to getting that downtime to where it’s just removing the parts you need to remove, put the new one on and go.”
Q. – What is HercFusion?
A. – HercFusion is a suite of tools utilizing AI to optimize aircraft maintenance, particularly for the C-130J Super Hercules.
Q. – What data does HercFusion analyze?
A. – HercFusion analyzes data from 3 million C-130J flight hours, including information from 600 sensors generating 3GB of data per flight hour.
