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Practical Reliability Engineering (O'Connor, Kleyner, 2012)
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With emphasis on practical aspects of engineering, this bestseller has gained worldwide recognition through progressive editions as the essential reliability textbook. This fifth edition retains the unique balanced mixture of reliability theory and applications, thoroughly updated with the latest industry best practices.

Practical Reliability Engineering fulfills the requirements of the Certified Reliability Engineer curriculum of the American Society for Quality (ASQ). Each chapter is supported by practice questions, and a solutions manual is available to course tutors via the companion website.

Enhanced coverage of mathematics of reliability, physics of failure, graphical and software methods of failure data analysis, reliability prediction and modelling, design for reliability and safety as well as management and economics of reliability programmes ensures continued relevance to all quality assurance and reliability courses.

Notable additions include:

  • New chapters on applications of Monte Carlo simulation methods and reliability demonstration methods.
  • Software applications of statistical methods, including probability plotting and a wider use of common software tools.
  • More detailed descriptions of reliability prediction methods.
  • Comprehensive treatment of accelerated test data analysis and warranty data analysis.
  • Revised and expanded end-of-chapter tutorial sections to advance students’ practical knowledge.

The fifth edition will appeal to a wide range of readers from college students to seasoned engineering professionals involved in the design, development, manufacture and maintenance of reliable engineering products and systems.

p.65 Whilst the mathematical methods described in this chapter can be useful for providing insights and for forecasting, it is important that their limitations are appreciated. They are mathematical models, and they do not necessarily reflect reality in the way deterministic, physics-based formulae do.
 
p.135 In engineering and science we use mathematical models for prediction... For a mathematical model to be accepted as a basis for scientific prediction, it must be based upon a theory which explains the relationship.
 
p.136 As Niels Bohr, the famous Danish physicist once jokingly said 'Prediction is very difficult - especially if it is about the future.'
 
p.274 It is not normally practicable to plan a test strategy which will provide high theoretical error coverage, and the test time would be exorbitant.
 
p.400 Generally, the earlier a defect is detected, the lower will be the cost... Therefore the test strategy must be based on detecting and correcting defects as early as practicable

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