This edition first published 2019
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Library of Congress Cataloging‐in‐Publication Data
Names: Todinov, M. T., author.
Title: Methods for reliability improvement and risk reduction / Michael
Todinov, Oxford Brookes University, UK.
Description: Hoboken, NJ, USA : Wiley, 2019. | Includes bibliographical
references and index. |
Identifiers: LCCN 2018033729 (print | LCCN 2018036493 (ebook | ISBN
9781119477310 (Adobe PDF | ISBN 9781119477594 (ePub | ISBN 9781119477587
(hardcover
Subjects: LCSH: Reliability (Engineering | Risk management. | System
failures (Engineering
Classification: LCC TA169 (ebook | LCC TA169 .T649 2019 (print | DDC
620/.00452–dc23
LC record available at https://lccn.loc.gov/2018033729
Cover Design: Wiley
Cover Illustration: © Michael Todinov
To the bright memory of my mother
The common approach to risk reduction is domain‐specific and relies exclusively on detailed knowledge from a specific domain. Measures specific to the domain are selected for reducing the risk and risk reduction is conducted exclusively by the experts in the domain. The underlying argument is simple yet powerful. Why should, for example, a welding specialist or automotive engineer listen to and seek advice from a general risk expert on how to improve the reliability of the welds or the reliability of a car? After all, the risk expert is not normally familiar with the welding or automotive technology.
This argument contributed to creating the illusion that efficient risk reduction can be delivered successfully solely by using methods offered by the specific domain without resorting to general methods for risk reduction. This led to a situation that in many domains, even the existence of a general risk science has been forgotten. In textbooks on design of machine components, for example, there is hardly any mention of general methods for improving reliability and reducing the risk of failure.
The price for this illusion is that many industries have been deprived of effective risk reducing strategy and solutions. The same mistakes are made again and again, resulting in numerous accidents and inferior products and processes, associated with high risk of failure.
An important contributing reason for this highly undesirable situation is the absence of a framework of domain‐independent methods that could provide vital methodological knowledge in reliability improvement and risk reduction.
With the exception of a very few simple and well‐known domain‐independent methods for risk reduction, such as implementing redundancy, strengthening weak links, upgrading with more reliable components, simplification of components, systems and operations, and condition monitoring, the framework of domain‐independent methods for risk reduction is missing. The absence of a framework of domain‐independent risk reduction methods diminishes significantly the importance of risk science and poses serious questions about whether it actually adds value to various areas of human activity.
Consequently, proposing a framework of domain‐independent methods for improving reliability and reduce risk was the primary motivation behind writing this book.
In this book, methods and principles related to improving reliability and reducing risk that can be classified as domain‐independent are first reviewed and their limitations discussed. Next, new domain‐independent principles and methods for reliability improvement and risk reduction are introduced, with a detailed discussion of the mechanisms through which they reduce risk.
The methods of reliability improvement and risk reduction presented in this book are based on a large number of available solutions, most of which came from mechanical engineering. Each of the available solutions was analysed for recurring reliability‐enhancing patterns and invariants. A certain level of abstraction was used to strip available solutions from the specific mechanical engineering context and uncover the underlying patterns governing the reliability improvement and risk reduction.
From the analysis of available solutions, various patterns and invariants emerged which were captured and distilled into categories, classes, and individual techniques. The application of the distilled new methods and principles has been illustrated with numerous real‐life application examples and case studies. Many of the domain‐independent methods reduce risk at no extra cost. This is a significant advantage to many traditional methods for reducing risk (e.g. redundancy, upgrading components, condition monitoring) which are associated with substantial investment.
The proposed framework of domain‐independent risk reducing methods is not a substitute for domain‐specific methods. It rather serves as a powerful enhancement of the domain‐specific risk reduction and helps to obtain superior solutions.
The framework of domain‐independent methods and principles for risk reduction proposed in this book prompts design engineers not to limit themselves to a few familiar domain‐specific methods for improving reliability and reducing risk which often lead to solutions that are far from optimal. Using appropriate combinations of domain‐independent and domain‐specific methods brings superior results.
Consequently, the proposed domain‐independent methods form an important part of risk science and firmly support the design for reliability and the decision making in the presence of uncertainty.
The proposed framework will enhance the reliability of products and operations for any company and organisation. To any company, reliability is one of the most important attributes of its products. High product reliability means high company reputation, high customer satisfaction, low warranty costs and repeat business. For a company, this translates into a big competitive advantage and secure market position. Low product reliability means financial losses, human injuries and fatalities, and damaged environment and infrastructure. For companies, this translates into a loss of reputation, loss of market share and, ultimately, a loss of business.
The framework of domain‐independent methods for risk reduction proposed in this book provides the basis for a strong interdisciplinary research. Researchers and engineers, after receiving training in domain‐independent risk reduction methods, are capable of solving complex reliability improvement problems in their specific industries/domains. In turn, the problems encountered in the specific industry/domain stimulate further development of the domain‐independent reliability improvement and risk reduction methods. This creates a positive self‐reinforcing feedback loop which benefits both the industry and the reliability and risk science.
The proposed framework of domain‐independent reliability improving methods works particularly well in improving the reliability of existing designs. In this respect, the author's experience in teaching these methods to engineering students shows that after minimal initial training in domain‐independent methods, students are capable of significantly improving the reliability of engineering designs of their choice by original and effective solutions based on these methods.
The domain‐independent methods for reliability improvement and risk reduction, are analogous to the proof techniques in mathematics. Proofs consist of a finite number of ideas and techniques (e.g. proof by contradiction, proof by contrapositive, mathematical induction, the extreme principle, the pigeonhole principle, proof based on parity, proof based on continuity of functions, probabilistic proof, etc.). Just as studying general proof techniques ensures success in building sound mathematical proofs, studying the domain‐independent methods for improving reliability and reducing risk ensures success in designing capable and reliable products.
It is the author's firm belief that the domain‐independent methods for reliability improvement and risk reduction should not only be an integral part of the reliability and risk science, they should also be an integral part of the education of every design engineer.
In conclusion, I thank the acquisition editor, Anne Hunt, the project editor, Jemima‐India Kingsly, the copyeditor Wendy Harvey and the production editor Sathishwaran Pathbanabhan at John Wiley & Sons for their excellent work and cooperation. My thanks also go to my many colleagues from universities and the industry for their useful suggestions and comments.
Finally, I acknowledge the immense help and support I received from my wife, Prolet, during the writing of this book.
Michael Todinov
Oxford, 2018