Objective Comparison of Confidence Bound Methods for Binomial Series System Reliability

Abstract

Obtaining lower confidence bounds on the reliability of a series system remains a problem of interest. Engineers and practitioners desire methods with good properties to obtain lower confidence bounds when only component-level binomial test data are available. With numerous methods proposed in the literature–none of which are uniformly superior–it can be an overwhelming task to select the method which best handles the scenario at hand. We develop a software tool in R (available in the “serieslcb” package) through which users can discover the methods that best suit their situation. The tool runs user-defined simulations and then ranks the best performing methods based on objective comparisons utilizing a delta coverage metric. This article outlines the methods and comparison strategy implemented in the package. It also discusses the design of the software tool and illustrates it with an example.