Test Plans Overview
 

Use Minitab's test planning commands to determine the sample size and testing time needed to estimate model parameters or to demonstrate that you have met specified reliability requirements.

A test plan includes:

·    The number of units you need to test

·    A stopping rule - the amount of time you must test each unit or the number of failures that must occur

·    Success criterion - the number of failures allowed while the test still passes (for example, every unit runs for the specified amount of time and there are no failures)

Three kinds of test plans are available: demonstration, estimation, and accelerated life.

Demonstration test plans

Use demonstration test plans to determine the sample size or testing time needed to demonstrate, with some level of confidence, that the reliability exceeds a given standard.

There are two types of demonstration tests:

·    Substantiation tests provide statistical evidence that a redesigned system has suppressed or significantly reduced a known cause of failure. You are testing:

H0: The redesigned system is no different from the old system.

H1: The redesigned system is better than the old system.

·    Reliability tests provide statistical basis that a reliability specification has been achieved. You are testing:

H0: The system reliability is less than or equal to a goal value.

H1: The system reliability is greater than a goal value.

You can rewrite these hypotheses in terms of the scale (Weibull or exponential distribution) or location (other distributions), a percentile, the reliability at a particular time, or the mean time to failure (MTTF). For example, you can test whether or not the MTTF for a redesigned system is greater than the MTTF for the old system.

Minitab provides an m-failure test plan for substantiation and reliability testing. If more than m failures occur in an m-failure test, the test fails.

Estimation test plans

Use estimation test plans to determine the number of test units that you need to estimate percentiles or reliabilities with a specified degree of precision. Estimation test plans are similar to classical sample-size problems, but computations are more intensive because the data are usually censored. Use estimation test plans to answer questions such as:

·    How many units must I test to estimate the 10th percentile with a 95% lower confidence bound within 100 hours of the estimate?

·    How long must I run the test to estimate the reliability at 500 hours with a 95% lower confidence bound within 0.05 of the estimate?

Accelerated life test plans

Use accelerated life test plans to determine the number of units to test and how to allocate those units across stress levels for an accelerated life test or to determine the standard error for the parameter you wish to estimate given a fixed number of test units. Use accelerated life test plans to answer questions such as:

·    How many units must I test to estimate the 10th percentile with a 95% upper confidence bound within 100 hours of the estimate?

·    What is the best allocation of 20 units across 3 stress levels in order to estimate the reliability at 1000 hours?

·    Twenty units are available for testing. What standard error can you expect for the estimate of the 500-hour reliability?

To obtain an accelerated test plan, you provide the stress values and, optionally, the proportionate allocation of test units. Minitab evaluates the resulting plans and displays the "best" plans with respect to minimizing the variance.