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management, implementation of Electronic Work Instructions and optimal inclusion of additional data elements
management, implementation of Electronic Work Instructions and optimal inclusion of additional data elements
Apr 03, 2025
In the fast-paced world of aviation, predictive maintenance has emerged as a game-changer, effectively bridging the gap between traditional reactive maintenance methods and a more proactive, data-driven approach.
Boeing's senior technical fellow, Darren Macer, emphasizes the critical role of data in the aerospace industry:
Data has become the lifeblood of the aerospace industry. We strive to enhance aircraft systems and components to provide more sensor data, enabling analysis that supports increasingly accurate and valuable insights on the aircraft's operational performance. The focus has led to a growing emphasis on evaluating predictive model performance, specifically prediction accuracy and the actions taken from alerts. This focus is reshaping feedback loop data sharing for predictive models, necessitating collaboration among airlines, OEMs, suppliers, MROs, and parts providers to achieve greater success.
In this article, we will share insights into Boeing's alerting strategy, the process of creating new alerts, and our methods for measuring the effectiveness of deployed alerts, as well as highlight some success stories. Additionally, we will discuss how we are leveraging diverse data sources and expanding our partnerships.
The evolution of predictive maintenance in aviation
The journey of predictive maintenance in aviation has been nothing short of remarkable. We have transitioned from a reactive maintenance model, primarily driven by fault data, to a proactive maintenance strategy informed by comprehensive aircraft and operational data, domain expertise, and advanced data science techniques. These advancements enable the creation and delivery of predictive alerts and notifications, which operators actively receive and act upon. This proactive approach allows components to be removed based on condition before failure, thereby reducing operational disruptions and overhaul costs.
Looking ahead, the future of predictive maintenance holds even greater promise. With the integration of prescriptive analytics, comprehensive fleet health data, and advanced decision-support systems—such as condition-based scheduled maintenance and digital twins—we are poised to redefine operational efficiency in aviation.
Alerting strategy
Boeing aircraft generate an immense volume of data in various formats, each offering unique insights to support predictive maintenance. This data can come from the Aircraft Condition Monitoring Function (ACMF), where we can identify exact signatures, or from high-rate, high-fidelity data sources.
Our engineering and data science teams are collaborating with bus-native rate data from all available sensors to gain a comprehensive understanding of operations. They are also utilizing lower-speed, full-flight data from a subset of parameters (such as Quick Access Recorder (QAR) or Continuous Parameter Logging (CPL) data) to generate and validate prognostics. Additionally, we are working on moving data collection and logic onboard the aircraft to enhance our predictive maintenance capabilities.
Content creation
At Boeing, we are committed to advancing predictive maintenance through innovative techniques and technologies that enhance our customers' operational efficiency and aircraft reliability. We recognize that predictive maintenance is a collaborative effort. While individual groups can create valuable content, the greatest benefits arise when engineers and data scientists from operators—who possess practical operational experience—and OEMs—with deep domain knowledge—partner together. This collaboration, coordination, and cooperation with the supply chain are essential for achieving maximum success in predictive maintenance.
Alert lifecycle
When an alert is issued, customers face a decision: do they need to respond to the alert? Our Airplane Health Management (AHM) model managers have diligently worked to track and improve alert utilization metrics. These metrics monitor our customers' overall usage of AHM and their responses to warnings or alerts regarding issues detected on the aircraft.
The AHM team has been collaborating closely with customers to enhance the AHM experience and reduce clutter, providing a streamlined process that allows customers to derive value from every alert in their workflow. This improvement process has involved internal adjustments to AHM logic, modifying alert frequency, and fine-tuning alerts to align with our customers' preferences.
Beyond aircraft data
The Boeing Predictive Maintenance team is actively researching and validating advanced diagnostic and prognostic procedures for various components that have undergone comprehensive health checks. Subsequent inspections have revealed increased values correlating with degradation, leading to proactive removals for detailed teardowns.
Robust on-wing diagnostic and prognostic procedures are central to Boeing's predictive maintenance strategy, enhancing customer trust in alerts and addressing gaps in available on-wing sensors. Our customers, suppliers, and Boeing continue to derive increasing value from leveraging new technologies to assess the health of both our latest and legacy aircraft. In2025, our engineering teams will focus on generating new advanced diagnostic procedures utilizing cutting-edge sensor-based hardware to optimize airline operations further.
Predictive maintenance in action
A recent collaboration between Boeing and a 787 operator exemplifies the power of predictive maintenance. We addressed a key component reliability issue in the environmental control system.
The operator completed extensive research using CPL data and identified a failure signature to identify mechanical degradation of a motor-driven compressor. Boeing and the operator worked together to validate the prognostic and developed an onboard ACMF report to expand the coverage and effectiveness of the approach.
The new report and alert will be made available to all AHM customers and provide relief for a significant in-service issue on the 787. This partnership exemplified the importance of collaboration between Boeing and our customers to ensure that predictive maintenance content is able to navigate lifecycle milestones from offboard research to onboard, real-time alerting.
While some airlines are just beginning their journey with predictive maintenance, others have established mature programs with advanced capabilities. This transformation is a collaborative effort that requires teamwork across various departments and the industry, as no single individual, group, or company possesses all the necessary data, knowledge, or capabilities.
Discover more
Are you interested in learning more about Boeing's predictive maintenance solutions? Check out our Airplane Health Management and Insight Accelerator for unrivaled decision support and insight into your operational efficiency. Join us as we continue to revolutionize aviation through the power of predictive maintenance!