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 Accelerated Life Data Analysis Case Studies

ALTA 7 Case Studies
 


Case Study 7: Accelerated Life Test Plan

Software Used: 
ALTA 7 or
 ALTA 7 PRO

[Download ALTA 7 Example File (*.ralp)


Background
A reliability group in a semiconductor company is planning an accelerated test for an electronic device. 30 test units will be employed for the test and the test is planned to last for 600 hours. Temperature and voltage have been determined to be the main factors affecting the reliability of the device. The normal use conditions of the devices are 300K for temperature and 4V for voltage. The purpose of the experiment is to estimate the B10 life of the device. The reliability engineer wants to use a three-level optimum plan because it will be easier to manage than a five-level test plan.  

Existing Information
Based on engineering knowledge, data from a previous design and data from a pilot test, the following information is available:

  • An Arrhenius model is assumed for the life-stress relationship associated with temperature and is accurate up to 360K.
  • A power model is assumed for the life-stress relationship associated with voltage and is accurate up to 10V.
  • The beta parameter for the underlying Weibull distribution is estimated to be 3.
  • The probabilities of failure for the product at the end of the test are estimated as follows:
    • Stress 1 = Usage Stress, Stress 2 = Usage Stress: 0.02
    • Stress 1 = Highest Stress, Stress 2 = Usage Stress: 0.9
    • Stress 1 = Usage Stress, Stress 2 = Highest Stress: 0.6

Analysis
Step 1: Using ALTA 7 or ALTA 7 PRO, the analyst adds a Test Plan to a project. The known parameters of the test are entered in the Setup Window as shown in Figure 1.

Figure 1     

Accelerated Test Plan Setup Window

Step 2: The analyst generates the Test Plan, as shown in Figure 2.

Figure 2      [Enlarge]

Figure 2: Click to Enlarge

The Test Plan can be evaluated by solving for any one of three criteria (confidence level, bounds ratio or sample size) given the two other criteria. The bounds ratio is the ratio of the upper confidence bound to the lower confidence bound on Tp (the estimate of the time when the specified percentage of the units will have failed at use stress).

In Figure 3, a confidence level of 0.9 and a sample size of 30 units are specified. The bounds ratio is calculated to be 1.92.

Figure 3    

Solving for bounds ratio.

In Figure 4, a bounds ratio of 1.5 and a confidence level of 0.9 are specified. The sample size is calculated to be 78 units.

Figure 4    

Solving for sample size.

In Figure 5, a sample size of 30 units and a bounds ratio of 1.5 are specified. The confidence level is calculated to be 69.34%.

Figure 5    

Solving for confidence level

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