*System Reliability Theory: Models and Statistics Methods*, by Arnljot Høyland and Marvin Rausand was published in 1994. We present here an extract from the Preface together with extracts from some reviews of this work. We also present an extract from a review of the second edition which was published in 2004 after the death of Arnljot Høyland.

**1. Preface.**

At the same time the book has been developed as a reference and handbook for industrial statisticians and reliability engineers.

The reader ought to have some knowledge of calculus and of elementary probability theory and statistics.

In the first five chapters we confine ourselves to situations where the state variables of components and systems are binary and independent. Failure models, qualitative system analysis, and reliability importance are discussed. These chapters constitute an elementary, though comprehensive introduction

**to**reliability theory. They may be covered in a one-semester course with three weekly lectures over fourteen weeks.

The remaining part of the book is somewhat more advanced and may serve as a text for a graduate course. In Chapter 6 situations where the components and systems may be in two or more states are discussed. This situation is modelled by Markov processes. Renewal theory is treated in Chapter 7, and dependent failures in Chapter 8. A rather broad introduction to life data analysis is given in Chapter 9, accelerated life testing in Chapter 10, and Bayesian reliability analysis in Chapter 11. The book concludes with information about reliability data sources in Chapter 12.

The book contains a large number of worked examples, and each chapter ends with a selection of problems, providing exercises and additional applications.

A forerunner of this book, written in Norwegian by professor Arne T Holen and the present authors, appeared in 1983 as an elementary introduction to reliability analysis. It was published by TAPIR and reprinted in 1988. However, we have rewritten all the chapters of the earlier book and added new material as well as several new chapters. The present book contains approximately twice as many pages as its forerunner and can be considered as a completely new book.

We have already tried much of the material in the present book in courses on reliability and risk analysis at the university level in Norway and Sweden, including continuing education courses for engineers working in industry. The feedback from participants in these courses has significantly improved the quality of the book.

*Trondheim 1993*

**2. Review by: William Q Meeker.**

*SIAM Review*

**38**(1) (1996), 175-177.

I enjoyed reading the book. I quickly gained an appreciation for the combination of practical and technical knowledge exhibited in the writing. New ideas are always motivated by clear real or realistic examples. The development is orderly and the writing style is clear and concise. Each chapter concludes with a number of interesting real/realistic problems that allow the reader to apply and explore the ideas that were developed in the chapter.

Most of the book deals with advanced probability models for reliability. The authors do, however, provide some coverage of analysis of reliability data. The mathematical level is higher than the standard engineering-oriented textbooks on the same subject. Readers without a strong calculus-based course in probability will have to struggle through some of the technical developments. Mathematical tools like matrix algebra, Laplace transform, and limiting arguments are used throughout. Høyland and Rausand cover all of the standard topics that one would expect to find in a book on system reliability. The book, however, is considerably broader than previous books in the area.

**3. Review by: Frank M Guess.**

*Journal of the American Statistical Association*

**91**(433) (1996), 436.

**4. Review by: Mark G Vangel.**

*Technometrics*

**38**(1) (1996), 79-80.

**5. Review by: Eric R Ziegel.**

*Technometrics*

**46**(4) (2004), 495.