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

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.

Bias Reduction of MLEs for Weibull Distributions under Grouped Lifetime Data

“…Furthermore, the bias of logĥ i obtained by the MMLE method is the largest among all of these methods. Freeman andVining (2010, 2013), and Kensler, Freeman, and Vining (2014) indicated that the twostage approach does produce biased estimates. Freeman (2011) examined the bias of the estimators via simulation.…”

“…Thus, the unbiasing factor method is preferred in order to achieve better results of estimation. Kensler, Freeman, and Vining (2014) noted that it may be possible to find an unbiasing factor for censored group data that would allow one to obtain an unbiased estimate of b. In this article, we try to reduce the bias of MLEs via an unbiasing factor method for grouped lifetime data.…”

An Overview of Designing Experiments for Reliability Data

“…Table 8 The second stage analysis does show that the temperature does have an important effect on the battery life. Kensler et al (2014) performed a simulation study to examine the performance of the two-stage method. They found that the two-stage method did an excellent job preserving the Type I error rate.…”

Recent Advances and Future Directions for Quality Engineering

“…There is a strong need for better experimental designs and analyses for reliability data that allow practitioners to identify the factors that produce the desired levels of reliability. Freeman and Vining and Kensler et al . discuss approaches for reliability experiments for censored Weibull data that take the experimental protocol into account.…”