Design of Experiments for Reliability Achievement

ENHANCES READERS' UNDERSTANDING OF EXPERIMENTAL DESIGN METHODS FOR SUCCESSFUL LIFE TESTING AND PRODUCT RELIABILITY IMPROVEMENT

Design of Experiments for Reliability Achievement illustrates how experimental design and life testing can be employed to grasp product reliability, thereby facilitating reliability enhancements. The book is structured into four sections.

The first section centres on statistical distributions and methods for modelling reliability data. The second section offers an overview of design of experiments, including response surface methodology and optimal designs. The third section explores regression models for reliability analysis, focusing on lifetime data. This part provides methods for accurately analysing data collected from a designed experiment. The final section integrates all prior content with customised experiments tailored for reliability testing. Throughout, there is a strong emphasis on reliability applications and methods, addressing both optimal and robust design with censored data.

To aid reader comprehension, examples and case studies are interspersed throughout the text to highlight critical factors in designing experiments, especially noting how life testing experiments are inherently distinct. The book includes numerous advanced exercises and solutions to enhance readers' grasp of real-world applications in experimental design and reliability. The authors make use of R and JMP^® software, with a supplemental website hosting the related data sets.

Authored by internationally recognised experts in experimental design methodology and reliability data analysis, the book covers topics such as:

• Introduction to reliability, lifetime distributions, censoring, and inference for parameters of lifetime distributions.
• Design of experiments, optimal design, and robust design.
• Lifetime regression, parametric regression models, and the Cox Proportional Hazard Model.
• Design strategies for reliability achievement.
• Accelerated testing, models for acceleration, and design of experiments for accelerated testing.

The text provides an accessible approach to reliability for readers with varying technical expertise levels. This book serves as a vital reference for statistical researchers, reliability engineers, quality engineers, and professionals in applied statistics and engineering. It is also a thorough textbook for upper-undergraduate and graduate-level courses in statistics and engineering.