Fundamentals of Reliability Engineering

Zusatztext

<p><b>Provides fundamentals of reliability engineering and illustrates practical applications in the area of parallel/distributed systems (Multistage Interconnection Networks)</b></p><p>The first part of the book (chapters 15) introduces the concept of reliability engineering, elements of probability theory, probability distributions, availability, and data analysis. The second part of the book (chapters 611) provides an overview of parallel/distributed computing, network design considerations, classification of multistage interconnection networks, network reliability evaluation methods, and reliability analysis of multistage interconnection networks including reliability prediction of distributed systems using Monte Carlo method.</p><p><i>Fundamentals of Reliability Engineering</i> meets the increasing demand for knowledge tools that practicing reliability professionals can use to optimize their reliability decisions. Reliability prediction is important as it determines the usability and efficiency of the network to provide services. Reliability evaluation methods discussed in this book can be applied to analyze the reliability of any other systems. As an example, reliability analysis of distributed systems that consist of layers of switching elements connected together in a predefined topology that provide the connectivity between the set of processors and the set of memory modules, are presented.</p>

Autorenportrait

<p><b>Indra Gunawan, PhD,</b> is a Senior Lecturer and Coordinator of Postgraduate Programs in Maintenance and Reliability Engineering in the School of Applied Sciences and Engineering at the Federation University, Australia. He completed his PhD degree in industrial engineering from Northeastern University, USA. Prior to joining Monash University, he served as a faculty member in the Department of Mechanical and Manufacturing Engineering at Auckland University of Technology, New Zealand. His main areas of research are maintenance and reliability engineering, project management, application of operations research, operations management, applied statistics, probability modeling, and engineering systems design. His work has appeared in many peer-reviewed journals and conference proceedings.</p>

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