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Traditional Reliability Growth Analysis

Quick Calculation Pad (QCP)

QCP Calculations and Plots for Traditional RGA

RGA includes a Quick Calculation Pad (QCP) for computing useful metrics, as well as multiple plots that allow you to visualize the results of your analyses. This topic describes the calculations and plots you can obtain from traditional reliability growth analysis (i.e., the analysis of developmental testing data with the assumption that fixes are applied immediately after a failure and before testing resumes).

Note: When you analyze data from multiple systems, RGA combines the data to create a single equivalent system. Any plots generated for the combined data set and analyses via the Quick Calculation Pad will be based on the equivalent system. See Times-to-Failure Data from Multiple Systems for more information about how the software combines the data for analysis.

QCP Calculations

You can open the Quick Calculation Pad (QCP) by choosing Growth Data > Analysis > Quick Calculation Pad or by clicking the icon on the control panel.

To perform a calculation, select the appropriate option and enter any required inputs in the Inputs area, then click Calculate. For more detailed information about all the options available in the QCP, see Quick Calculation Pad (QCP).

The types of calculations available depend on the selected data type:

Times-to-failure data types

Discrete data types

Reliability data type

Plots

You can create plots by choosing Growth Data > Analysis > Plot or by clicking the icon on the control panel.

This section describes the types of plots you can create for traditional reliability growth analysis. The scaling, setup, exporting and confidence bounds settings are similar to the options available for all other RGA plot sheets. For more information on these common options, see Plots.

The types of plots you can create depend on the selected data type:

Times-to-failure data types

Discrete data types

Reliability data type

Tip: RGA includes two additional plot utilities you can use across all types of data: the overlay plot, which allows you to compare different data sets or models; and the side-by-side plot, which allows you to display different plots of a single data set all in a single window for easy comparison.

 

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