MicrosoftProductionEvidence: Low40/100

EPCOR boosts predictive maintenance and efficiency in aircraft support operations

EPCOR, a subsidiary of Air France-KLM, modernized its maintenance operations for aircraft Auxiliary Power Units (APUs) by migrating legacy systems to a Microsoft Azure cloud environment. Facing outdated, manual processes and inconsistent ERP data, EPCOR set out to build a robust, AI-enabled infrastructure. They implemented Dynamics 365 Finance & Operations, established a data warehouse, and replaced SAP Business Objects with Power BI for better data visualization. A modernized proprietary tool, Prognos for APU, was migrated to Azure, centralizing and harmonizing aircraft component data for real-time analytics. Collaboration with data scientists led to development of new AI algorithms for predictive maintenance, enabling earlier detection of APU faults—including subtle issues not detected by traditional monitoring. The cloud solution allowed EPCOR to forecast shop visits, optimize inventory and turnaround times, rapidly scale IT resources as their business grew, and improve service reliability. Key benefits include greater operational efficiency, scalability for future growth, and the ability to support over 100 airlines globally with advanced insights.

Organization
EPCOR
Location
Netherlands

Reported outcomes

Strategic outcomes

New product / capabilityEnabled AI predictive maintenanceSpeed & agilityOptimized turnaround timesScale & capacityBuilt scalable cloud infrastructureCustomer experience & trustImproved service reliability for airlines
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
EPCOR
Provider
Microsoft
Maturity
Production
Linked source
pulse.microsoft.com

Key benefits include greater operational efficiency, scalability for future growth, and the ability to support over 100 airlines globally with advanced insights

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

  • 1AI-Driven Predictive Maintenance for Aircraft APUs
  • 2Centralized Cloud-Based Monitoring of Aerospace Components
  • Legacy ERP system created inconsistent data usage and inefficiencies.
  • Reliance on manual, spreadsheet-based analysis limited predictive maintenance capabilities.
  • Difficulty integrating and extracting value from dormant and disconnected data sources.
  • Growing business required a scalable and future-proof IT infrastructure.
  • Reactive maintenance led to higher repair costs and potential delays.
  • Migrated key business and analytic workloads to Microsoft Azure cloud.
  • Implemented Dynamics 365 Finance & Operations to streamline processes.
  • Replaced SAP analytics with Power BI for improved visualization and reporting.
  • Modernized and centralized proprietary APU monitoring tools for advanced analytics.
  • Developed AI algorithms for predictive maintenance in collaboration with data scientists.
  • Reduced turnaround times and optimized inventory through better forecasting.
  • Enabled proactive maintenance and earlier detection of equipment faults.
  • Facilitated business growth with scalable cloud infrastructure.
  • Improved productivity and flexibility for a workforce that grew from 30 to nearly 200 staff.
  • Enhanced service reliability for over 100 airlines worldwide.
Architecture

Data from aircraft APUs is collected using Prognos for APU, migrated and centralized on Microsoft Azure. From there, Dynamics 365 Finance & Operations handles core processes. Data warehouse and analytics are handled with Power BI, replacing older SAP tools. The cloud-based environment supports AI-driven predictive algorithms, processes multiple data sources, and integrates maintenance forecasting for EPCOR and its airline customers.

Sources & evidence1
Evidence: Low40/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Technical implementation details available
Publisher: pulse.microsoft.com

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