Advanced Reliability Models and Maintenance Policies

✍ Scribed by Toshio Nakagawa (auth.)

Publisher: Springer-Verlag London
Year: 2008
Tongue: English
Leaves: 251
Series: Springer Series in Reliability Engineering
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Reliability theory is a major concern for engineers and managers engaged in making high quality products and designing highly reliable systems. Advanced Reliability Models and Maintenance Policies is a survey of new research topics in reliability theory and optimization techniques in reliability engineering.

Advanced Reliability Models and Maintenance Policies introduces partition and redundant problems within reliability models, and provides optimization techniques. The book also indicates how to perform maintenance in a finite time span and at failure detection, and to apply recovery techniques for computer systems. New themes such as reliability complexity and service reliability in reliability theory are theoretically proposed, and optimization problems in management science using reliability techniques are presented.

Advanced Reliability Models and Maintenance Policies is an essential guide for graduate students and researchers in reliability theory, and a valuable reference for reliability engineers engaged both in maintenance work and in management and computer systems.

✦ Table of Contents

Front Matter....Pages i-ix
Introduction....Pages 1-5
Redundant Models....Pages 7-37
Partition Policies....Pages 39-57
Maintenance Policies for a Finite Interval....Pages 59-76
Forward and Backward Times in Reliability Models....Pages 77-100
Optimum Retrial Number of Reliability Models....Pages 101-122
Optimum Checkpoint Intervals for Fault Detection....Pages 123-147
Maintenance Models with Two Variables....Pages 149-186
System Complexity and Entropy Models....Pages 187-203
Management Models with Reliability Applications....Pages 205-234
Back Matter....Pages 235-246

✦ Subjects

Quality Control, Reliability, Safety and Risk; Engineering Design; Operations Research/Decision Theory; Optimization

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