Use Nonparametric
Distribution Analysis to estimate the reliability of a product when no parametric distribution adequately
fits your data.
Depending on which nonparametric method you choose, you can do the following:
- Estimate the percentage of items that will fail or survive at various time intervals
- Display hazard plots and survival plots to view the failure and survival probabilities
- Test the equality of the survival curves for multiple samples
You can also use a nonparametric distribution analysis to validate and compare the results from a parametric distribution analysis. A nonparametric distribution analysis is less efficient than a parametric analysis with an appropriate distribution model, and thus often produces wider confidence intervals. However, because a nonparametric analysis does not require fitting any distribution to your data, its results will not be adversely affected by a poor distribution fit.
Use this analysis for exact failure times or for any censoring scheme.
- Exact failure data
- Record the failure time at a fixed point in time before the end of the study
or reliability test
- Right-censored data
- Record a time when the unit still survived at the end of the study or
reliability test. For example, a patient may quit a study before it ends, or
a unit is still operating after the allocated testing time. The exact
failure time is unknown but will certainly occur beyond the allocated study
time.
- Interval-censored data
- The exact failure time is unknown, but it occurred in a known interval. For
example, a unit was still operating at 12 when the reliability engineer left
for a mid-day break. Upon the engineer’s return at 12:30 they noticed that
the unit has failed. Thus, the unit failed in the interval starting at 12
and ending at 12:30.
- Left-censored data
- Left-censored data is a special case of interval-censored data point where
the beginning point of the interval may be time 0 or may be unknown. The
engineer only knows that the unit failed by some specific time since the
beginning of the reliability test.
In this analysis, interval censoring allows for the specification of left-censored data
and data that combine different types of censoring. For more information, go to Data censoring.
When your product fails in different ways, use a failure mode analysis to evaluate the impact of each type of failure on the overall reliability. Each failure mode is assumed to be independent. By analyzing each failure mode individually, you can more easily prioritize your improvement efforts.
Tip
The analysis stores a reliability data definition that includes the sample columns
and the censoring scheme. Select the definition to quickly run Distribution ID Plot, Distribution Overview Plot, Parametric Distribution Analysis, and Nonparametric Distribution Analysis on the same data.
Where to find this analysis
To perform a nonparametric distribution analysis, choose .
When to use an alternate analysis
- Parametric methods provide more precise results and
estimate more types of functions when the assumed parametric distribution model
is correct. Therefore, if you can fit a parametric distribution to your data,
use Parametric Distribution
Analysis.
- To determine whether a parametric
distribution adequately fits your data, use Distribution ID
Plot.
