Predictive Process Management for aircraft MRO

This project was for summer term 2020, you CAN NOT apply to this project anymore!

Results of this project are explained in detail in the final documentation and presentation.

Motivation and Value Proposition 

  • Aircraft Maintenance is both time critical and costly, while also heavily regulated by federal authorities; thus, delays in Aircraft MRO („Maintenance, Repair, Overhaul“) may result in delays, profit loss and customer dissatisfaction
  • Material and tool availability has been identified as one important driver of delayed maintenance 
  • Materials and Tools are often transferred between stations on short notice or ordered outside the standard lead time, causing high costs
  • Improved material/tool availability and increased maintenance punctuality have significant impact on intra-day punctuality and customer satisfaction
  • Process prediction allows better steering of planning/procurement tasks and reduces rework and effort in maintenance operations
  • Improved process handling plays well with CityLine’s continuous improvement program and other process improvement initiatives (e.g. OptiOps) 
  • Advanced process steering reduces need for material and tool transfer and canal so help to reduce emissions and improve sustainability

Content / Deliverables

  • Process analysis: As-is analyses of the current process and implications on material availability, punctuality and costs.
  • Process prediction: Design and implementation of a prediction model for the aircraft MRO process: identify proper data points, link process and master data, choose and implement proper prediction algorithms (e.g. clustering – freely selectable)
  • Process steering: Define measures to avoid process deviations collaboratively with business areas and implement proper monitoring of measures.
  • Operations: For all three topics, keep maintainability, performance and scalability in mind; the prediction model must be adaptable to more/different aircraft