We have created a series of examples to illustrate the AEMPS value through demonstrating the input-output data
Inputs:
The entire AEMPS example input data is put in an Excel workbook similar to the one that we have structured for easy
data collection to use AEMPS OnDemand routinely.
Download demonstration input data (MS Excel 144 KB)
Outputs:
We have prepared the actual AEMPS outputs for the example input data.
View ERS one-parameter analysis
View ERS two-parameter analysis
View ERS cumulative distribution function
Please note that R Square determines which method, one-parameter or two-parameter, is best suited to use for
removal forecasting and lifetime optimization. The method with a higher R Square represents the reliability
characteristics more accurately, and is recommended for use in other applications.
View ERF scheduled removal analysis
View ERF short-term removal forecast (example 1)
View ERF short-term removal forecast (example 2)
View ERF long-range removal forecast
Please note that ERF is applied to the data for engines that are currently in operation.
Two examples are provided for applying ELO:
Example 1: Engine No. xxx184
Simulation of Engine Build was first applied to determine the unit cost for the decisions that were made without
using ELO to optimize the engine lifetime.
View ELO Simulation of Engine Build (example 1)
Then, Minimum Build Optimizer was used to identify the life-limited parts replacement that would result in
lowering the unit cost.
View ELO Minimum Build Optimizer (example 1)
View ELO Minimum Build Optimizer engine profile (example 1)
As can be observed, applying ELO resulted in reducing the unit cost by $12.15 per flying hour ($22.11 per cycle).
Example 2: Engine No. xxx771
Simulation of Engine Build was first applied to determine the unit cost for the decisions that were made without
using ELO to optimize the engine lifetime.
View ELO Simulation of Engine Build (example 2)
Then, Minimum Build Optimizer was used to identify the life-limited parts replacement that would result in lowering
the unit cost.
View ELO Minimum Build Optimizer (example 2)
View ELO Minimum Build Optimizer engine profile (example 2)
As can be observed, applying ELO resulted in reducing the unit cost by $65.49 per flying hour ($119.20 per cycle).
View SEPS optimization report (example 1)
View SEPS optimization report (example 2)
SEPS resulted in saving one engine in the near term and four in a longer term. It also redeployed the allocation for
increasing the network protection level and fill rate.
