AST SafeScan Friction Forecaster™

With SafeScan Friction Forecaster™, you can know what surface conditions will be – and what to do about it

We leverage the latest machine learning and AI technology

AST’s Friction Forecaster™ Model provides reliable friction forecasts based on a number of input parameters that include, among others:

• actual past, actual present, and forecasted weather conditions collected automatically and aggregated from 13 different weather sources
• location direction
• surface type of the runway
• and aircraft type for which the prediction is made

The machine-learning algorithm was developed and tested on the AST database containing millions of landings. It delivers a reliable and stable forecasting platform tested and validated on all major airports/runways in the US.

Early warnings – seeing the future so you can prepare for it

Our friction forecasts provide airports and carriers with multiple opportunities to make well-informed decisions that can help increase safety, operational efficiency, and cost savings. For example:

• Early warnings can help airports stay ahead of winter storms and apply preventative anti-icing treatments, rather than deicing treatments once snow and ice have already bonded to the pavement.
• Preemptive anti-icing treatments improve safety and should reduce airport costs, given that deicing normally requires a larger quantity of FPD to be effective.
• Enhanced situational awareness gives airports and airlines the ability to collaborate through ATO, A/P to shift runway maintenance to more optimal times in order to avoid closures during high traffic or high-value traffic. This helps limit delays and diversions, improving schedule reliability.
• Insight into current landing conditions and developing trends will greatly aid airlines and the airports from which they operate – they can recognize inevitable diversions sooner and take steps to reduce associated costs and disruptions.
• Benefits include:
  • Improved flight ops and operational control decisions
  • Better payload weight management
  • Cost savings from reduced holding patterns and fewer diversions due to greater runway uptime
  • Optimized landing configurations
  • Reduced taxi time

Request a free demo