1.

3.

Choose Monitoring at Intervals if you can estimate when the experiment will fail. Enter the number of inspections, the time of the first inspection, and the time between inspections.
Choose Continuous Monitoring if you are unsure of when the experiment will fail.
4.

Click Continue.

6.

Click Continue.

Time range of interest are values for which you want an estimated probability of failure. For example, if you are interested in the probability of failure by 100,000 hours, then enter 100,000 for both the lower and upper ranges.
Probability of interest is the value for which you want an estimated time of failure. For example, if you are most interested in obtaining the time until 10% of units fail, then enter 0.1.
Length of Test is the length of time to run the experiment.
Number of Units Under Test is the number of units in the experiment. If augmenting a previous experiment, enter the number of units from the previous experiment plus the number of units that you want to run for the next experiment. If designing an initial experiment, enter the number of units that you want to run.
8.

Click Continue.

9.

Click Update Profiler to update the profiler if changes are made to the distribution choice, means, variances, design choices, or candidate runs.

10.

Click Make Design to create the optimal design and display the results.

The Design report gives the expected number of failures for each level of the acceleration factor. Also given is the probability that none of the units at this setting will fail.
The Parameter Variance for Optimal Design report gives the variances and covariances for the acceleration model parameters for the optimal design. These values are valid under the assumption that the values for the prior mean and variance are correct. These values can be compared to those under Parameter Variance for Balanced Design to determine whether the optimal design is able to reduce the parameter variances more than the balanced design.
The Optimality Criteria report gives the values of the optimality criterion for the optimal design. For more information about the optimality criterion, see Platform Options.
The Make Design button updates the optimal design if any changes are made to the distribution choice, prior means or variances, design choices, or candidate runs.
The Make Test Plan button creates a data table with the acceleration factor levels and the number of units to include in the experiment for each level.
The Make Table button creates a table that can be used for data collection during the experiment.