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A reliability engineer wants to investigate the deterioration of an insulation that is used for electric motors. The motors normally run between 80 and 100° C. To accelerate the rate of failures, the engineer collects failure times for the insulation at four abnormally high temperatures: 110, 130, 150, and 170° C.
You can use this data to demonstrate Accelerated Life Testing and Regression with Life Data. The relationship between the Arrhenius temperature and the failures is linear.
| Worksheet column | Description |
|---|---|
| Temp | The temperature that the insulation was exposed to for the test: 170, 150,130, or 110 |
| ArrTemp | The Arrhenius temperature of the test temperature |
| Plant | The manufacturing plant where the insulation was made: 1 or 2 |
| FailureT | The test time in hours for each motor |
| Censor | Indicates whether the insulation failed or survived the test: F = failed or C = did not fail |
| Design | The temperature endpoints for the motors. The motors normally run between 80oC and 100oC |
| NewTemp | The temperature for predicting failures at normal temperatures |
| ArrNewT | The Arrhenius temperature of the prediction temperature |
| NewPlant | The manufacturing plant for estimating failures |
Use columns 8 and 9 to estimate the failures from each manufacturing plant at normal temperatures.
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