Case Study

Genpact's strong engineering, analytics and technology capabilities help a leading aircraft engine manufacturer revamp business operations for efficiency, growth, and agility

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Client: A leading US-based aircraft engine manufacturer

Industry: Aerospace

Business need addressed: Transformed fleet management operations

Genpact solution: Genpact's Lean DigitalSM approach integrated insights from client's asset data into reimagined operations and made them predictive and proactive

Business impact:

  • Lower cost of maintenance, and higher asset uptimes (time on wing)
  • Cut cost of fleet support operations by 40%

A leading US-based aircraft engine manufacturer needed to use asset data to predict engine/parts failures and act proactively to schedule timely preventive maintenance, maintain optimal inventory levels for critical spares and alert airlines on engine performance issues. Genpact's Lean DigitalSM approach, engineering, analytics and technology capabilities created an operating model that enabled data-to-insight and insight-to-action at scale, with process redesign, effective automation and global delivery.


Business challenge

  • Rapid growth in installed base stretched the capacity of fleet support operations to the limit
  • Exponential growth in volume of data (but limited insight due to noise caused by poor data quality), fragmentation of data, and lack of scalable analytics
  • Loss of revenues and poor customer experience due to the inability to leverage asset data to predict engine/parts failures and act proactively to schedule timely preventive maintenance, maintain optimal inventory levels for critical spares, and alert airlines on engine performance issues
  • Expensive and time-consuming manual effort in filtering out relevant alerts for customer notification 

Genpact solution

  • An operating model that enabled data-to-insight and Insight-to-Action at scale, with process redesign, effective automation and global delivery
  • An outcome-focused approach that worked across silos to streamline processes and map relevant data (and its sources) to target technology interventions in an agile way
  • Leveraged advanced industrial internet platforms (Predix from GE) to capture and analyze asset-monitoring data
  • Forecasting models integrated multiple operating parameters to predict part failure and remaining useful life of critical parts
  • Machine learning algorithms replaced manual effort to screen false alerts
  • Integrated feedback loop to product design teams, providing real-time part performance and failure analytics to make design changes

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Business impact

  • Lower cost of maintenance, and higher asset uptimes (time on wing) through accurate parts failure and remaining life forecasts, preemptive maintenance, fewer unscheduled maintenance events and optimal spare availability, resulting in higher revenue and profits
  • Cut cost of fleet support operations by 40% through a combination of redesigned processes, automation and global delivery
  • Scalable solution capable of supporting growth in fleet cost effectively
  • Satisfied customers with on-time and safer flight operations with proactive alerts to airlines on engine performance
  • More competitive products with insights for product enhancements, engineering tooling, and design for manufacturability

This case study was first featured in management consulting firm Zinnov's annual GSPR 2015 report.

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