The Rail Life Forecasting Model (RailLife) was developed by ZETA-TECH Associates, Inc. and is an analytical software tool for helping users determine when rail requires replacement based on historical degradation and predefined safety/maintenance thresholds. RailLife is an interactive user-friendly Windows™ application that allows the user to make the most efficient decisions pertaining to rail maintenance.

RailLife utilizes statistical and empirical techniques for determining rail degradation based on actual inspection information. Two primary techniques are utilized, the Weibull statistical technique rail fatigue and multivariate regression techniques for rail wear. Both techniques make use of inspection car information (ultrasonic test results and rail profile measurements) for the statistical analyses.

The analysis steps utilize historical railroad data for rail installation (type, date, etc.), traffic (annual/cumulative MGT), geometry (curvature, grade, etc.), and rail degradation (defects and wear). Homogeneous segments of rail are developed and these segments are processed and analyzed using a hierarchy of techniques to determine the controlling failure mechanism and rate of degradation. Based on these rates, and predefined safety/maintenance thresholds, a forecast replacement date can be determined for each rail segment.

The primary interface screen for RailLife is shown below.

This main menu allows the user to select files to analyze, perform analysis steps, edit analysis parameters, and generate reports. As can be seen form this screen, several data tables are required as input and the output is stored to separate tables for further analysis and reporting. Each table in the database can be viewed as shown in the data table view port.

One of the interesting and unique features of RailLife is the ability to edit several analysis parameters in order to understand the effects these parameters have on the resulting rail life. An example of the wear safety/maintenance thresholds is shown below. As can be seen from this figure, these thresholds vary by usage (annual MGT), rail section, and head/gage and effect when rail should be replaced.

An example of the analysis results are shown below.