Vol. 63, No. 3, November 2017
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BOOK REVIEW

Reliability and Availability Engineering:
Modeling Analysis, and Applications

Kishor Trivedi and Andrea Bobbio
Cambridge University Press, 2017

The increasing dependence on the technological infrastructure, especially in advanced economies, is not without its perils. Even short outages in the infrastructure can have drastic consequences, ranging from economic losses in the least, all the way to loss of human life in the worst case. It is thus imperative that our complex and critical infrastructure, including the likes of the Internet, transportation, energy supply, communications, health, financial services and commerce be designed and implemented with assurance of a certain level of dependability. While the aforementioned scenarios are typical, how can their dependability be guaranteed a priori with a certain level of confidence? This makes it imperative that suitable techniques that enable us to assess, predict, verify and validate the level of reliability, availability, safety and maintainability of these products, services and infrastructures be developed. Now there are many books that provide some insights into the methods of dependability assurance but none of them provide a very comprehensive set of techniques in the context real-life applications. The plethora of analytical techniques available for the evaluation of reliability and availability leaves a practitioner often in a quandary, unable to figure out the most suitable approach to analytically evaluate the system under investigation

The primary aim of this book is to comprehensively consider in details all techniques together showing similarities and differences and pointing out the pros and cons of each approach. Furthermore the book not only covers classical techniques like reliability block diagrams, faulttrees, network reliability and Markov models but also more advanced techniques like non exponential models and new approaches and analysis techniques, like the use of Binary Decision Diagrams, Dynamic Fault Trees, Bayesian Belief Networks and stochastic Petri nets. Furthermore, the book particularly addresses the multi-level modeling for the analysis of large systems combining different modeling formalisms. Another unique feature of the book is that there are three chapters exclusively devoted to dealing with non-exponential distributions.

A major strength of the book is a large number of solved examples, a significant number of real case studies and many problems that can be assigned as homework. Some of the examples are strung through different chapters so as to show the application of different techniques on the same basic example. We are planning a solution manual and a set of power point slides for instructors using this book as a text. The software packages SHARPE and SPNP can be obtained by contacting the first author. Three key topics that are not covered, except in a few examples, due to size limitations are: statistical techniques, discrete-event simulation and optimization

Over forty years of experience of both of the two authors in developing techniques, software applications and real-life experience and in consultancy and teaching, is distilled in this book. The book can be used for a two semester course on reliability engineering; it can be used by practicing engineers as it is comprehensive and contains many real-life case studies; and it can be used a reference by researchers in reliability engineering.

The book is divided in 6 Parts and 18 Chapters along the following contents table.

Part I Introduction 1
  1. Dependability
  2. Dependability Evaluation
  3. Dependability Metrics Defined on a Single Unit
 3
15
40

Part II Non-State-Space (Combinatorial) Models
101
  1. Reliability Block Diagram
  2. Network Reliability
  3. Fault Tree Analysis
  4. State Enumeration
  5. Dynamic Redundancy
 103
147
198
268
283

Part III State-Space Models with Exponential Distributions
299
  1. Continuous-Time Markov Chain: Availability Models
  2. Continuous-Time Markov Chain: Reliability Models
  3. Continuous-Time Markov Chain: Queuing Systems
  4. Petri Nets
301
353
418
448

Part IV State-Space Models with Non-Exponential Distributions
481
  1. Non-Homogeneous Continuous-Time Markov Chains
  2. Semi-Markov and Markov Regenerative Models
  3. Phase-Type Expansion
 482
501
545

Part V Multi-Level Models
569
  1. Hierarchical Models
  2. Fixed-Point Iteration
570
625

Part VI Case Studies
637
  1. Modeling Real-Life Systems
 638

Author Index
Subject Index