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Publication date: 06/21/2023

Reliability Life Testing

Use the Reliability Life Test Interval Explorer to explore the sample size, study length, or precision needed for a reliability life test. Select DOE > Sample Size Explorers > Reliability > Reliability Life Testing.

Reliability life tests are used to estimate failure times and failure probabilities of a product. The Reliability Life Test explorer uses expected confidence intervals to define the precision of the estimates. These estimates are based on a fitted failure distribution.

Interval Explorer for Parametric Reliability Life Test Planning Settings

Set study assumptions and explore sample sizes using the radio buttons, text boxes, and menus. The profiler updates as you make changes to the settings. Alternatively, change settings by dragging the cross hairs on the profiler curves.

Interval Type

Lower Bound

Specifies a one-sided lower interval.

Upper Bound

Specifies a one-sided upper interval.

Interval

Specifies a two-sided interval.

Preliminary Information

Alpha

Specifies the confidence level, 1 - Alpha. The default alpha level is 0.05 for a 95% confidence interval.

Distribution

The assumed failure distribution. Distributions available are: Weibull, Lognormal, Frechet, and Loglogistic. For more information about these distributions, see Statistical Details for the Life Distribution Platform in Reliability and Survival Methods.

Censoring Time

The amount of time available to run the reliability test. Units surviving past this time are censored.

Quantile

(Available only for response type set to quantile.) The quantile to estimate, enter as a whole number.

Failure Time

(Available only for response type set to failure probability.) The time at which to calculate the failure probability.

Response Type

Quantile

Select to estimate the quantile of the life distribution.

Failure Probability

Select to estimate the probability of failing before a given time point

Interval Metric

Interval Ratio

The ratio of the upper to the lower interval limits.

Relative Width

The width of the interval relative to the magnitude of the estimate.

Interval Explorer for Parametric Reliability Life Test Planning Profiler

The profiler enables you to visualize the impact of sample size assumptions on the interval calculations.

Solve for

Enables you to solve for the sample size, location parameter, or scale parameter.

Interval Ratio

(Available only for interval metric set to interval ratio.) Defines precision as the ratio of the interval endpoints.

Relative Width

Defines precision as the width of the confidence interval or the difference between the upper and lower limits.

Sample Size

The number of units to include in the reliability test.

Location Parameter

The location parameter for the failure distribution.

Note: The Location field is denoted Weibull α when the Distribution is set to Weibull.

Scale Parameter

The scale parameter for the failure distribution.

Note: The Scale field is denoted Weibull β when the Distribution is set to Weibull.

Interval Explorer for Parametric Reliability Life Test Planning Options

The Explorer red triangle menu and report buttons provide additional options:

Simulate Data

Opens a data table of simulated data based on the explorer settings. View the simulated response column formula for the settings used.

Make Data Collection Table

Creates a new data table that you can use for data collection. The table includes scripts to facilitate data analysis.

Save Settings

Saves the current settings to the Saved Settings table. This enables you to save a set of alternative study plans. See Saved Settings in the Sample Size Explorers.

Help

Opens JMP help.

Statistical Details for the Interval Explorer for Parametric Reliability Life Test Planning

The reliability test plan is designed to estimate either a quantile:

Equation shown here

or a failure probability:

Equation shown here

at a specified level of significance with an assumed failure time distribution and precision measure. Φ() is the standard cumulative distribution function of the assumed failure time distribution with location parameter μ and scale parameter σ. Wald confidence intervals and the precision measure define precision as a function of t (time) and n (sample size). Numerical methods are used to solve for the desired quantity.

For more information about calculations in JMP, see Barker (2011, Section 6)

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).