Predictive Process Management for aircraft MRO

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