Reliability: Analysis and Measure

Reliability data isn't amenable to treatment with the ubiquitous normal distribution, a fact that should catch the attention of any practicing engineer with only that bullet in his gun.   Reliability data has other distinguishing features.  The data are usually censored, which means the exact failure times are not known so the observations can only provide bounds on the actual failure times. Inferences and predictions usually require extrapolations, making engineering and physics-based modeling an important adjunct to statistical methods.  Whereas many *statistical* problems focus on parameter estimation (e.g.: mean, standard deviation), these are not of primary interest to engineers who need specific measures of product reliability (e.g.: failure probabilities, life distribution quintiles, failure rates).

Reference:

Meeker and Escobar, Statistical Methods for Reliability Data,  Wiley, 1998.  This is an excellent book.  If your bookseller is out of stock, you can get a copy quickly from amazon.com.