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.
|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.