ST Engineering Launches Predictive Maintenance Tool With Japanese Airlines

Credit: Zipair Tokyo

For global, full-service MROs, predictive maintenance tools have become almost table stakes for securing major contracts. ST Engineering has now joined providers like Lufthansa Technik and AFI-KLM E&M in offering a service that detects anomalies in component performance and predicts remaining useful life to aid maintenance decisions.

The new service, called Component Health Management, was launched in a five-year maintenance-by the-hour (MBH) contract, starting in September 2021, to provide integrated component support for all Boeing 787s belonging to Japan Airlines (JAL) and its low-cost subsidiary, Zipair Tokyo. ST Engineering already had an MBH contract to support components on the airline’s 737-800s.

The new contract with JAL and Zipair is among the first applications of Component Health Management. “We have two other new customers who have signed up for our on-wing component health and reliability management program with predictive capability,” explains an ST Engineering spokesperson.

The MRO started developing Component Health Management in 2019, and its development remains an ongoing, iterative process. “The analytics model . . . will continue to get better as the platform handles more aircraft data with more customers and users coming onboard,” the spokesperson notes.

ST Engineering developed Component Health Management completely in-house. Its developers did make use of standard off-the-shelf software and tools, such as the general-purpose programming language C#, Microsoft Azure’s SQL, UiPath, which helps with robotic process automation, and reusable chunks of code retrieved from Python libraries. The system also uses Tableau Software to enable users to see predictions and the data patterns behind predictions.
Developers worked extensively with both airline customers and many specialists within ST Engineering itself, including aircraft engineers, data analysts, reliability engineers and supply chain management engineers.

To implement predictive maintenance, a key consideration is availability of component failure and related sensor data. ST Engineering collaborates with its customers to select the components they wish to monitor based on both the availability of sensor and failure data and the impact of a particular component’s failure on operations. Components identified for Component Health Management may thus vary by aircraft type. So far, components selected for Component Health Management have included integrated drive generators, skin air valves, air turbine starters and valves and engine-driven hydraulic pumps.

The ST Engineering spokesperson says key data for these components will come from sensor data related to the components, component defect logs, shop finding reports, mean time between unscheduled removals, mean time between failures and other reliability data.

ST Engineering says Component Health Management should help reduced defect-related delays and cancellations, thus avoiding revenue losses. In addition, it estimates that by turning unscheduled maintenance into scheduled maintenance, the service could eventually reduce MRO costs by up to 60%.

ST Engineering clearly views the early contracts and applications as just a start. “We definitely have plans to expand the use of the platform to more customers . . . Having more participating customers would lead to a wider pool of components available for analysis,” the spokesperson emphasizes. “Such traction will further contribute to the robustness and maturity of the platform to glean valuable MRO insights.”

Over the longer term, ST Engineering also plans to use the new predictive platform to support its integrated engine support programs.