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Reliability Analysis for Engineers: An Introduction

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  • Leitch, Roger D.

Abstract

In ordinary life "reliability" is an ephemeral but desirable property of a machine or service that is generally judged in a very subjective manner. For an engineer reliability has large cost and sometimes safety implications; it is therefore very important to be able to quantify it. This book is an introduction to reliability analysis aimed at engineers (not statisticians). As such it begins by assuming no prior statistical knowledge. It teaches by examples taken from engineering problems. Exercises are built around real machines and events and the solutions given illuminate the subject. Being able to quantify reliability allows engineers to quantify its financial implications in terms of maintenance policies, running costs, and spares stockholding. In safety critical situations (transport or military equipment) the implications are wider. In any complex project it is extremely important to be able to make reliability predictions.

Suggested Citation

  • Leitch, Roger D., 1995. "Reliability Analysis for Engineers: An Introduction," OUP Catalogue, Oxford University Press, number 9780198563716.
    • Handle: RePEc:oxp:obooks:9780198563716
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    Cited by:

    1. Cayo Cid de França Moraes & Plácido Rogério Pinheiro & Ivo Goncalves Rolim & Jose Luis da Silva Costa & Marcos da Silva Elias Junior & Sidney Jose Meireles De Andrade, 2021. "Using the Multi-Criteria Model for Optimization of Operational Routes of Thermal Power Plants," Energies, MDPI, vol. 14(12), pages 1-17, June.
    2. Balaraju Jakkula & Govinda Raj Mandela & Suryanarayana Murthy Chivukula, 2022. "Reliability, availability and maintainability (RAM) investigation of Load Haul Dumpers (LHDs): a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 504-515, February.
    3. Hernandez-Perdomo, Elvis & Guney, Yilmaz & Rocco, Claudio M., 2019. "A reliability model for assessing corporate governance using machine learning techniques," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 220-231.

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