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In a zero-failure reliability demonstration test (RDT), the engineer aims to demonstrate a specified target metric (e.g., reliability at a specific time with a given confidence level) by testing a specified number of units for a predetermined time. If no failures occur, then the target metric is demonstrated. This method has been adapted for scenarios where the target metric can be demonstrated even if some failures occur, so long as a specified number of allowable failures is not exceeded. For example, in a demonstration test where the number of allowable failures is 2, the target metric is demonstrated if no more than 2 failures occur during the test.[1]
ReliaSoft's RDT tool can assist the user in designing a demonstration test by solving for various values related to the test, such as sample size, required test time, the demonstrated reliability and the confidence level at which the target reliability will be demonstrated.
Tip: This tool could determine, for example, that if you assume your units follow a Weibull distribution with a shape parameter of 2 and you tested 10 units for 150 hours and none failed during the test, then you would demonstrate a 90% reliability at 100 hours with 90% confidence. It does not, however, calculate the probability that one or more units might actually fail during the test. If you wish to estimate whether a failure is likely to occur, one option is to use the Expected Failure Time Plot to estimate the first failure time based on the assumed distribution and parameters.
Follow the steps outlined below to use the tool:
Select the appropriate test design option from the Test Design Method drop-down list on the control panel and enter all the required inputs. When you change the test design option, the required inputs on the RDT sheet will change. The four options are the following:
The Parametric Binomial option determines what test duration or sample size will be required to demonstrate either reliability at a specific time or a specified mean time to failure. To use this option, you must provide an estimate of the underlying life distribution's shape parameter.
Note: You can get the parameters and time units from a calculated data sheet in the current project by clicking the Get Failure Distribution from Folio icon on the control panel.
If you are demonstrating the reliability at a specified time, enter the time in the At this Time field. If you used the Get Failure Distribution from Folio option, this value will initially be set to the time at which a product with the calculated life distribution would have the reliability that you specified.
If you are demonstrating the mean time to failure, enter the mean time in the Demonstrate this MTTF field. If you used the Get Failure Distribution from Folio option, this value will initially be set to the MTTF that a product with the calculated life distribution would have.
You can also create a table that displays a range of test duration values as a function of sample size and number of allowable failures. The table can also display a range of required sample size values as a function of test time and number of allowable failures. After you create this table, you can also create a plot displaying the same information. This provides a quick way to consider many possible test plan scenarios without having to perform each calculation individually.
The Non-Parametric Binomial option does not require a life distribution. It solves for the demonstrated reliability, confidence level or sample size that is associated with a specified test design.
The use of this option assumes that the time at which the reliability is demonstrated is equal to the specified test time multiplied by the specified acceleration factor. For example, if the acceleration factor is 1, then the time at which reliability is demonstrated equals the test duration. If the acceleration factor is 2, then the time at which the reliability is demonstrated is double the test duration, and so on.
The Exponential Chi-Squared option determines the total accumulated test time that will be required to demonstrate a specified metric.
The total accumulated test time is equal to the total amount of time experienced by all of the units on test. For example, if the total accumulated time is 100 hours, then you could test 1 unit for 100 hours, or you could test 2 units for 50 hours each, or you could test 5 units for 1 hour each and 1 unit for 95 hours.
This option is based on the chi-squared distribution, and it is only for products that have an assumed exponential life distribution (i.e., products with a constant failure rate).
The Non-Parametric Bayesian option solves for the demonstrated reliability or confidence level that can be expected from a specified test design. It can also solve for the sample size needed to demonstrate a target reliability at a specified confidence level. To use this option, you must have some prior information with which you can estimate the product’s reliability.
With this option, you will need to specify whether the source of prior information is expert opinion (i.e., engineering experience) about the reliability of the entire system or prior testing at the subsystem level. This is done in the Prior information about the failure rate behavior area of the RDT sheet.
If you have experience regarding the system as a whole, choose Expert opinion on reliability. Then, enter worst case, expected and best case estimates of the product's reliability.
If you have prior test data for subsystems that compose your system, then choose Prior tests at the subsystem level. In the Number of subsystems drop-down list, choose the number of different subsystems that you will enter data for. After you select the number of subsystems, click the Edit Bayesian Subsystems icon on the control panel to open a window you can use to enter the prior test data.
Alternatively, you can click the appropriate cell on the RDT sheet to enter the information directly into the sheet, as shown next.
Like the non-parametric binomial option, the use of the non-parametric Bayesian option assumes that the time at which the reliability is demonstrated is equal to the specified test time multiplied by the specified acceleration factor.
The following chart shows the information that each method can provide. The ReliaWiki resource portal has more information on these methods at: http://www.ReliaWiki.org/index.php/Reliability_Test_Design.
Metric to demonstrate: | Can solve for: | |
Parametric Binomial | The reliability at a specific time or Mean time to failure (MTTF) |
The test time for a specified sample size or The sample size for a specified test time |
Non-Parametric Binomial | Reliability at test time (if acceleration factor = 1) |
The demonstrated reliability or The associated confidence level or The necessary sample size |
Exponential Chi-Squared | The reliability at a specific time or Mean time to failure (MTTF) |
The total accumulated test time |
Non-Parametric Bayesian | Reliability at test time (if acceleration factor = 1) |
The demonstrated reliability or The associated confidence level or The necessary sample size |
In the Units field of the control panel, define the units of time that will be used in the test.
If you selected to solve for sample size, select whether sample sizes will be displayed as integers in the Display Options area.
In the Acceleration Factor field of the control panel, enter the acceleration factor associated with the stress level that will be used in the test, if applicable.
The acceleration factor is obtained by dividing the product’s life at the use stress level by its life at the accelerated stress level to be used in the test, if applicable. For example, if the product has a life of 100 hours at the use stress level, and it is being tested at an accelerated stress level which reduces its life to 50 hours, then you would enter 2 in the Acceleration Factor field. If you are testing units under normal operating conditions, then the acceleration factor is 1.
Click Calculate to solve for your selected value.
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