Full Support for Traditional Reliability Growth Analysis
RGA provides a comprehensive array of analysis options for situations when it is appropriate to assume that all permanent design improvements are applied by the end of the test (test-fix-test). To accommodate the wide variety of potential test/data collection scenarios, the software supports a flexible selection of data types, growth models and calculated analysis results. This includes:
When you have data from developmental testing in which the systems were operated continuously until failure, you can use the Crow-AMSAA (NHPP) or Duane models. RGA provides a choice of data types for individual or grouped failure times, and also for combining data from multiple identical systems. This can include situations where:
- All systems operate concurrently so the operating time of each non-failed system is the same as the time recorded for the failed system.
- You have recorded the exact operating times for both the failed and non-failed systems.
- You have recorded the calendar date for each failure so the software can estimate the operating times of the non-failed systems based on the average daily usage rate for the relevant time period.
With the Crow-AMSAA (NHPP) model, RGA offers additional analysis options for certain situations.
- Gap Analysis: If you believe that some portion of the data is erroneous or missing, this feature allows you to retain the gap interval’s contribution to the total test time without making assumptions about the actual number of failures during that time period.
- Change of Slope: If a major change in the system design or operational environment has caused a significant change in the failure intensity observed during testing, a single model may not provide a good fit for the data. In such cases, RGA can split the data into two segments and apply a separate Crow-AMSAA (NHPP) model to each segment.
Discrete Data (Also Called Attribute, One-Shot or Success/Failure Data)
When you have data from one-shot (pass/fail) reliability growth tests (and depending on the data type), RGA supports the Standard Gompertz, Modified Gompertz, Lloyd-Lipow or Logistic models in addition to Crow-AMSAA and Duane.
For discrete data, the software provides a choice of data types that can handle tests in which a single trial is performed for each design configuration, multiple trials per configuration, or a combination of both. RGA also supports Failure Discounting if you have recorded the specific failure modes from sequential one-shot tests.
When you simply wish to analyze the calculated reliability values for different times/stages within developmental testing, you can use the Standard Gompertz, Modified Gompertz, Lloyd-Lipow or Logistic models.
Calculated Results and Plots for Traditional RGA
For traditional reliability growth analysis (and depending on the data type and RGA model), you will be able to:
- Calculate the MTBF, failure intensity or reliability for a given time/stage.
- Determine the amount of testing that will be required to demonstrate a specified MTBF, failure intensity or reliability.
- Estimate the expected number of failures for a given time/stage.
The Quick Calculation Pad (QCP) has been updated and redesigned in the Synthesis version. The new interface provides a "Calculation Log" that works like a paper roll in an adding machine, allowing you to record the results from a series of different calculations and then copy/paste the information as needed.