Predictive Maintenance: A day in the life of a Safran Fleet Manager
The Fleet Manager is the aircraft’s Condition Supervisor. His mission is to monitor the health of the landing systems under contract. He plays an essential role in the delivery of the predictive maintenance service to our customers that currently concerns the Airbus A350 program. What does Predictive Maintenance do? It allows to anticipate the likelihood of imminent equipment failure to Safran Landing Systems engineers who will then alert the airline and recommend proactive maintenance action. This way, it helps to reduce the number of unscheduled events.
Read on to find out more about our Fleet Manager's day-to-day activities at Safran Landing Systems.
9.00am: Weekly review with technical experts
On arrival at the office, Alice participates in the Weekly Alert Review meeting she leads. All the women and men involved in delivering the predictive maintenance service are present: Service Owner, Design Engineers and Product Support Engineers. Each active alert logged in the software is reviewed and an immediate decision is taken. In practice, the indicators characterizing an anomaly are visualized to estimate the probability and imminence of an unscheduled event such as a fault message or a functional issue.
Today, the team has decided to continue monitoring an alert on a Brake Servovalve that does not represent an imminent risk. It is still too early to warn the customer. However, if the trend persists, Alice will alert the operator of the aircraft and provide advice on a suitable proactive maintenance action. The standard lead time to notify a customer is 30 days before the estimated occurrence of an event. This leaves enough time to schedule a ground slot, as well as the required parts, tools and resources.
Alice now focuses on another alert: a particular trend has been under investigation for several weeks and has shown further deterioration on a Park Brake Selector Valve: a notification will be sent right away to the customer to advise the replacement of the component (see example below).
Finally, to follow up on an alert sent the previous week about a Nose Wheel Steering Servovalve, the recommended corrective action has since been confirmed by the airline. The situation has now returned to normal, Alice will send a notification to formally close the case. Indeed, Safran Landing Systems not only warns the customer when a problem occurs, it also guarantees follow-up until actual resolution.
10.30am: Sending of notification and maintenance recommendations
Alice sends an ‘Alert Tracker’ to an Asian airline as decided during the joint weekly review. An Alert Tracker carries all the important information to notify the customer of an anomaly, whether routine or critical, depending on the urgency of the situation.
Most of the time the Alert Tracker is tagged 'ROUTINE' leaving 30 days for the airline to perform recommended maintenance actions. The 'CRITICAL' tag is used for rapidly deteriorating trends with a significant impact on operations.
Alice provides technical justifications and identifies the component supposedly causing the anomaly. A replacement is recommended 'at the next convenient opportunity'. In that case the part replacement is not an emergency and it can be carried out any time a different topic related intervention is scheduled.
Later on, the customer confirms that the equipment replacement is scheduled within days.
11.40am: Test & Work Report analysis
Alice has just received a Test & Work Report from Safran Landing Systems’ repair station in Molsheim, France. It relates to another case, an Alternate Brake Servovalve for which Safran Landing Systems issued an alert and advised the airline to carry out a part change. The report following the hydraulic test bench carried out to test the part revealed a significant drift in the pressure characteristic, outside of CMM (Component Maintenance Manual) limits, which fully explains the trend observed on the aircraft. This confirms the notification sent two months earlier. It thus prevented an unscheduled event and potential interruption to operations.
This analysis testify Safran Landing Systems' excellent service performance: over 90% of defects are confirmed in the workshop.
01.35pm: Sending out Weekly Fleet Reports
In the afternoon, Alice is busy editing and sending out Weekly Fleet Reports on their fleets to customers who have signed up for the service's “Premium” option. These reports summarize recent notifications sent, as well as emerging phenomena that could later on impact operations in the future. The benefit for airlines is to ensure that their inventory is sufficient to carry out the maintenance operations within the next 3 months.
03.17pm: An alert has just triggered on an aircraft
Alice immediately takes note of the alert! She consults the system parameters in the predictive maintenance software (see example below). The first step is to confirm the anomaly and assess its severity and urgency. As the case is particularly complex, Alice calls in the design office for an in-depth analysis.
Two hours later, the systems engineers confirm the problem on the equipment: from now on, the trend will be closely monitored to ensure the customer is notified in due time.
The working day of our Fleet Manager is a busy one: from monitoring equipment condition to sending alerts and recommendations. Alice is fully committed to ensuring operational excellence for our customers. Predictive maintenance enables to anticipate unscheduled events and ensure the continuity of our customers' operations, with ever-better aircraft availability.
The Predictive Maintenance service is part of Landing Life, Safran Landing Systems aftermarket support and services offer. Discover Landing Life global offer on Safran Website: Landing Life ®️ | Safran (safran-group.com)
To find out more about Predictive Maintenance on ATA32 systems:
- To request a demo of the service, contact our experts
- Visit the Predictive Maintenance service page: Safran (safran-group.com)
Join us at Safran. Job positions are available in the maintenance, repair and overhaul domain.
Predictive Maintenance
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