For reliability growth data analysis only.
Traditional reliability growth analysis is used to analyze data from tests where design fixes are incorporated during the observation period (the test-fix-test strategy). However, in actual practice, fixes may be delayed until after the end of the observation period (test-find-test), or you may implement some fixes during the observation period while delaying others (test-fix-find-test).
With the Crow Extended model, you can perform reliability growth projections, planning and analysis—which allows you to analyze test data from any or all of these strategies by providing additional information about the failure modes and the reliability growth management strategy (i.e., which modes are fixed and how effectively the design improvements reduce failure intensity). You can also use this model for data from fielded repairable systems in order 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.
Data types that can be used with the Crow Extended model
Classifying failure modes according to whether and when fixes will be implemented
Setting the effectiveness factors for delayed fixes
Using event codes to specify the type of event that each row in the data sheet represents (applies to the Multi-Systems with Event Codes data type only).
Analysis results for Crow Extended
Two examples of analysis with the Crow Extended model, including: