EMPIRICAL BAYES ESTIMATION OF THE RELIABILITY OF NUCLEAR-POWER-PLANT EMERGENCY DIESEL GENERATORS

For a binomial sampling model using pass/fail data and a beta prior di stribution, parametric empirical Bayes (FEB) point and credibility int erval estimates are provided for the time-and-diesel average emergency diesel generator (EDG) reliability to load-run on demand at 63 U.S. c ommercial nuclear power stations. For a geometric sampling model and a beta prior distribution, similar estimates of the time-dependent EDG- average reliability are also obtained for four plants. This is an expo sitory article that introduces seven practical steps, involving both m odel validation and inference, in applying modern FEB methods. It also illustrates some important advantages of using industry-wide data to make inferences on individual items.