Additional Tools

This chapter includes the following sections:

The RGA 7 software also offers a utility that allows you to use the non-homogeneous Poisson process model to design reliability demonstration tests for repairable systems.

When analyzing developmental systems for reliability growth and conducting data analysis of fielded repairable systems, it is often useful to experiment with various "what if" scenarios or put together hypothetical analyses before having available test data in order to find the best way to analyze data when they become available. With that in mind, RGA 7 offers applications based on Monte Carlo simulation that can be used in order to:

  1. better understand reliability growth concepts.
  2. experiment with the impact of sample size, test time and growth parameters on analysis results.
  3. construct simulation-based confidence intervals.
  4. better understand concepts behind confidence intervals.
  5. design reliability demonstration tests.

There are two applications of the Monte Carlo simulation in RGA 7. One is called Generate Monte Carlo Data and the other is called SimuMatic.