PREDICTIVE MAINTENANCE
How can integrating predictive analytics into fleet reliability management cut unscheduled maintenance costs by up to 50%?
PROBLEM
UNPLANNED MAINTENANCE COSTS
In 2018, the costs of addressing technical failures due to unplanned equipment breakdowns exceeded 20 billion USD globally for airlines, accounting for approximately 27% of all maintenance expenses. This had a direct impact on the efficiency of route networks, as nearly 3.8% of all flight delays and cancellations were caused by equipment failure-related incidents.
The number of unplanned aircraft failures is at a high level when there is no overall strategy within the fleet reliability program to perform predictive analysis, repair, and replacement of a component before it becomes involuntary.
CONSEQUENCES
CONSEQUENCES
- additional maintenance costs and extra time
- unplanned downtime of aircraft
- reduced commercial operation/disposal time
- increased number of delays due to technical reasons
- decrease in flight safety
SOLUTION
PREDICTIVE ANALYTICS
Predictive analytics-based maintenance is a strategy that leverages data and analytics to anticipate potential unit failures. Unlike traditional "reactive" maintenance, where repairs or servicing occur only after a component has failed, or "preventive" maintenance, where aircraft are serviced on a fixed schedule regardless of need, this approach focuses on addressing issues before they arise.
Implementation of predictive analytics in fleet reliability management processes can reduce unscheduled maintenance costs by 50%.
To reduce costs associated with unplanned failures and minimize their impact on airline operations, it is essential to implement a continuous process of monitoring and cross-referencing as much data as possible from aircraft systems, components, and sensors.
DATA SOURCES
To reduce costs associated with unplanned failures and minimize their impact on airline operations, it is essential to implement a continuous process of monitoring and cross-referencing as much data as possible from aircraft systems, components, and sensors.
DATA SOURCES
- ACARS
- QAR
- FDR
- TLB
- FLIGHT DATA
- CCL
PRODUCT
We offer a specialized AI and consulting product designed to identify components in a pre-failure condition and reduce the occurrence of unscheduled failures in aircraft equipment. Our approach combines proprietary software for analyzing large datasets with extensive engineering expertise.
- 60 CCLCCLthe number of CCLs in a fleet of 20 wide-body aircraft
- 90%PROXIMITYfault confirmation for pre-failure condition components
- 25% lessAOGfewer occurrences
- 7% lessDELAYdeduction in technical delays
FAQ
First, we'll work together to identify which specific defects are causing unplanned aircraft downtime and attempt to find correlations between defects, parameters, and feedback from pilots and engineers using neural network analysis tools. This initial assessment is completely free for the airline and will help determine if our product can truly benefit you.
While maintenance procedures already include monitoring the most critical components, they don't cover 100% of cases. As a result, operators still face unplanned failures that lead to delays, AOG situations, or even aviation incidents. Our solution is specifically designed to minimize these unplanned failures, which are the most costly for airlines in terms of time, money, personnel, and other resources. The earlier an operator can detect a trend toward failure, the more time they have to respond. This tool also allows for the prioritization of spare parts stock across the fleet based on the criticality of related system indicators.
Initially, preparing data may require additional resources if the operator hasn’t systematically organized data on FDR (Flight Data Recorder), failures, and delays. If the data is already organized, simply providing it to us in any format, but for a complete period of 6 months to 1 year, will be sufficient. After implementing the solution our team will independently convert standard airline data into a format suitable for ongoing analysis and monitoring.
It’s true that there are solutions on the market. However, our product stands out because we possess in-house engineering expertise to develop precise criteria for identifying pre-failure conditions of components. We have a team of experienced engineers who speak the same language as operators and understand all technical and organizational challenges.
Other products provide only software that can be used if the operator has already defined and developed exact criteria. This approach has proven to be impractical, as it fails to consider the many factors present in real-world operations.
Other products provide only software that can be used if the operator has already defined and developed exact criteria. This approach has proven to be impractical, as it fails to consider the many factors present in real-world operations.