One of the largest aircraft manufacturers used Momentum to determine more cost effective parts to replace expensive parts matching all engineering specifications.
Thousands of parts and millions of data points analyzed to build a machine learning model that groups aircraft parts matching all engineering specifications. The outcomes are then compiled, analyzed and presented on Momentum Insight for further decision making.
An aviation company needed to prioritize maintenance and replacement of parts to ensure no breakdowns and avoid expensive maintenance and replacement that was performed based on mean lifetime.
An accurate and timely prediction was needed to avoid premature replacement of parts. In addition, the system was able to give actionable insights into maintenance schedule by aircraft types, staffing and fuel costs.
This reduced the overall maintenance costs and provided improved scheduling for maintenance.