A Practitioner's Guide to Analyzing Reliability Experiments with Random Blocks and Subsampling

Abstract

ABSTRACT Reliability experiments provide important information regarding the life of a product, including how various factors affect product life. Current analyses of reliability data usually assume a completely randomized design. However, reliability experiments frequently contain subsampling, which represents a restriction on randomization. A typical experiment involves applying treatments to test stands, with several items placed on each test stand. In addition, raw materials used in experiments are often produced in batches, leading to a design involving blocks. This article proposes a method using Weibull regression for analyzing reliability experiments with random blocks and subsampling. An illustration of the method is provided. KEYWORDS: maximum likelihood estimationnonnormal dataregression estimationreliability estimationrestrictions on randomization