SSALTs are an alternative to apply stress to devices in a way that stress levels will increase at prespecified times step‐by‐step. For SSALTs, there are three fundamental models for the effect of increased stress levels on the lifetime distribution of a device: The tampered random variable model proposed by DeGroot and Goel (1979), the cumulative exposure model of Sedyakin (1966) and Nelson (1980); see also (Nikulin and Tahir, 2013), and the tampered failure rate model proposed by Bhattacharyya and Soejoeti (1989). All these models of SSALTs have been discussed extensively by many authors. Gouno (2001) analyzed data collected from SSALTs and presented an optimal design for SSALTs; see also Gouno (2007). Zhao and Elsayed (2005) analyzed data on the light intensity of light emitting diodes collected from SSALTs with four stress levels under Weibull and log‐normal distributions. For the case of exponential lifetime distribution, by considering a simple SSALT under Type‐II censoring, Balakrishnan et al. (2007) developed exact likelihood inferential methods for the model parameters; see also Balakrishnan (2008) for details, while Xiong et al. (2006) considered the situation when the stress changes from a low‐level stress to a high‐level stress at a random time.
1.4 Examples in Reliability and Survival Studies
1.4.1 Electro‐Explosive Devices Data
Fan et al. (2009) considered data, presented in Table 1.1, on 90 electro‐explosive devices under various levels of temperature at different inspection times. Ten devices under test at each condition were inspected to see whether there were any failures or not at each inspection time for each temperature setting. These data were then used to estimate the reliability of electro‐explosive devices at different mission times under the normal operating temperature.
Table 1.1 Failure records on electro‐explosive devices under CSALTs with temperature (K).
Source: Fan et al. (2009).
| Test group | Inspection time | Temperature | Number of samples | Number of failures |
|---|---|---|---|---|
| 1 | 10 | 308 | 10 | 3 |
| 2 | 10 | 318 | 10 | 1 |
| 3 | 10 | 328 | 10 | 6 |
| 4 | 20 | 308 | 10 | 3 |
| 5 | 20 | 318 | 10 | 5 |
| 6 | 20 | 328 | 10 | 7 |
| 7 | 30 | 308 | 10 | 7 |
| 8 | 30 | 318 | 10 | 7 |
| 9 | 30 | 328 | 10 | 9 |
1.4.2 Glass Capacitors Data
Zelen (1959) presented data from a life‐test of glass capacitors at four higher‐than‐usual levels of temperature and two levels of voltage. At each of the eight combinations of temperature and voltage, eight items were tested. We adopt these data to form one‐shot device testing data by taking the inspection times (hours) as
1.4.3 Solder Joints Data
Lau et al. (1988) considered data on 90 solder joints under three types of printed circuit boards (PCBs) at different temperatures. The lifetime was measured as the number of cycles until the solder joint failed, while the failure of a solder joint is defined as a 10% increase in measured resistance. A simplified dataset is derived from the original one and presented in Table 1.3, where two stress factors considered are temperature and a dichotomous variable indicating if the PCB type is “copper‐nickel‐tin” or not.
Table 1.2 Failure records on glass capacitors under CSALTs with two stress factors: temperature (K) and voltage (V).
Source: Zelen (1959).
| Test group | Inspection time | Temperature | Voltage | Number of samples | Number of failures |
|---|---|---|---|---|---|
| 1 | 450 | 443 | 200 | 8 | 1 |
| 2 | 400 | 453 | 200 | 8 | 0 |
| 3 | 350 | 443 | 250 | 8 | 0 |
| 4 | 300 | 453 | 250 | 8 | 1 |
| 5 | 450 | 443 | 300 | 8 | 3 |
| 6 | 400 | 453 | 300 | 8 | 4 |
| 7 | 350 | 443 | 350 | 8 | 3 |
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