Fielded Repairable Systems and Operational Testing
Repairable Systems Analysis with a Limited Data Set
Some of the models in RGA can be used to analyze data from repairable systems operating in the field under typical customer usage conditions. Such data might be obtained from a warranty system, repair depot, operational testing, etc.
Specifically, you can use the Power Law or Crow-AMSAA (NHPP) models for repairable system analysis based on the assumption of minimal repair (i.e., the system is "as bad as old" after each repair) to calculate a variety of useful metrics, including:
- Optimum overhaul time for a given repair cost and overhaul cost.
- Conditional reliability, MTBF or failure intensity for a given time.
- Expected number of failures for a given time.
- Time for a given conditional reliability, MTBF or failure intensity.
You can also use the Crow Extended model for fielded repairable systems if you want to evaluate the improvement (i.e., the jump in MTBF) that could be achieved by rolling out a set of fixes for all systems operating in the field.
Reliability Test Design for Repairable Systems
While ReliaSoft’s Weibull++ software provides a test design utility that's suitable to design a reliability demonstration test (e.g., "zero failure test") for non-repairable items, the test design utility in RGA has been designed specifically for repairable systems.
Redesigned in the Synthesis version, this tool uses the NHPP model to determine the test time required per system (or the number of systems that must be tested) in order to demonstrate a specified reliability goal, defined in terms of MTBF or failure intensity at a given time.
Operational Mission Profiles
When a system must be tested for a variety of different operational mission profiles, it can be a challenge to make sure that the testing is applied in a balanced manner that will yield data suitable for reliability growth analysis.
RGA's Mission Profile folios can help you to:
- Create an operational test plan that effectively balances all of the mission profiles that need to be tested.
- Track the expected vs. actual usage for all mission profiles and verify that the testing has been conducted in a manner that will yield data sets that are appropriate for reliability growth analysis.
- Automatically group the data at specified "convergence points" so the growth model can be applied appropriately (if there have been any significant variations from the plan).