Global Services
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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
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What sets it apart
Engineer-controlled alert creation
Engineers create, test, tune, and deploy alerts themselves rather than relying on data scientists or software developers.
AI-powered insight discovery
Built-in ML algorithms help uncover trends, anomalies, and developing issues hidden within operational data.
Flight and maintenance data together
Analyze maintenance records alongside QAR, CPL, and other operational data sources in one environment.
No data science team required
Engineers can uncover insights and create predictive alerts without coding, programming, or specialized analytics resources.
Airline-controlled intelligence
Create predictive alerts based on your operation’s unique aircraft, maintenance practices, and reliability challenges rather than relying solely on prebuilt models.
Boeing AHM integration
Connect predictive alerts with Boeing Airplane Health Management for centralized monitoring and visibility.
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Create custom alerts
Create, test, tune, and deploy predictive alerts tailored to your fleet, systems, and operational priorities. Engineers can build alert logic around specific components, failure modes, or degradation trends they want to monitor. Alerts can be refined over time as operating conditions and fleet behavior evolve.
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Discover hidden patterns
Use AI-powered analytics to uncover trends, anomalies, and degradation patterns hidden within flight and maintenance data. AHM Predictive Alerts Builder helps engineers identify relationships that would be difficult to detect through manual analysis alone. These insights can then be turned into predictive alerts that support earlier intervention.
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Analyze flight and maintenance data together
Combine QAR, CPL, maintenance, reliability, and other operational data sources in a single environment. By analyzing these data sets together, engineers gain a more complete understanding of aircraft performance, component health, and emerging maintenance risks. This provides the context needed to make more informed maintenance decisions.
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Guided insight discovery
Interactive workflows and visualizations help engineers explore data, validate findings, and identify developing issues without coding or specialized analytics expertise. Teams can move from data exploration to predictive alert creation within the same workflow. This reduces reliance on data scientists and accelerates adoption across engineering organizations.
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Optimize alert performance
Test and refine alert logic to improve accuracy and align with real-world operating conditions. Engineers can adjust thresholds, validate performance, and continuously improve alerts as new data becomes available. This helps reduce false positives while increasing confidence in predictive recommendations.
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Boeing AHM integration
Connect AHM Predictive Alerts Builder directly with Boeing Airplane Health Management to centralize predictive alerts and aircraft health information. Alerts created in AHM Predictive Alerts Builder can be monitored alongside Boeing-developed health monitoring capabilities in a single workflow. This gives maintenance teams greater visibility and operational context when prioritizing actions.
System integrations
Boeing product integrations
Connects directly with Boeing Airplane Health Management to centralize predictive alerts and aircraft health information in a single workflow.
Flight data sources
Analyzes recorded flight data, including QAR and CPL data.
Maintenance and reliability data
Correlates maintenance, reliability, and operational information to uncover deeper insights and improve predictive accuracy.
Why airlines choose AHM Predictive Alerts Builder
Reduce unscheduled maintenance
Identify developing issues earlier so corrective action can be planned before operational disruption, delays, or aircraft-on-ground events occur.
Get more value from existing data
Turn flight and maintenance data already generated across your operation into actionable maintenance intelligence without building new analytics programs.
Extend component service life
Identify degradation trends earlier and make more informed repair and replacement decisions to maximize component utilization.
Scale predictive maintenance without additional headcount
Enable engineering teams to create and manage predictive maintenance alerts without dedicated data scientists or specialized analytics resources.
Tailor predictive maintenance to your operation
Create and refine alerts based on your fleet, maintenance practices, and operational priorities rather than relying solely on generic models.
Improve aircraft availability
Reduce maintenance-driven disruptions and keep aircraft flying where they generate revenue.
Frequently asked questions
What is AHM Predictive Alerts Builder?
AHM Predictive Alerts Builder is an AI-powered analytics solution that helps airlines uncover insights from flight and maintenance data and create custom alerts for predictive maintenance.
What data does AHM Predictive Alerts Builder analyze?
AHM Predictive Alerts Builder analyzes recorded flight data, including QAR and CPL data, alongside maintenance, reliability, and other operational data sources.
How does AHM Predictive Alerts Builder support predictive maintenance?
The solution helps engineers identify patterns, trends, and developing issues within operational data and create alerts that support earlier maintenance intervention.
Do I need data scientists to use AHM Predictive Alerts Builder?
No. AHM Predictive Alerts Builder is designed for maintenance and reliability teams. Engineers can create, test, tune, and deploy predictive alerts without coding or specialized data science resources.
Who uses AHM Predictive Alerts Builder?
AHM Predictive Alerts Builder is designed for maintenance engineers, reliability engineers, technical services teams, and maintenance leaders responsible for aircraft reliability and performance.