Learning from Failures: Decision Analysis of Major Disasters.pdf

Learning from Failures: Decision Analysis of Major Disasters.pdf


Learning from Failures provides techniques to explore the root causes of specific disasters and how we can learn from them. It focuses on a number of well-known case studies, including: the sinking of the Titanic; the BP Texas City incident; the Chernobyl disaster; the NASA Space Shuttle Columbia accident; the Bhopal disaster; and the Concorde accident. This title is an ideal teaching aid, informed by the author's extensive teaching and practical experience and including a list of learning outcomes at the beginning of each chapter, detailed derivation, and many solved examples for modeling and decision analysis. This book discusses the value in applying different models as mental maps to analyze disasters. The analysis of these case studies helps to demonstrate how subjectivity that relies on opinions of experts can be turned into modeling approaches that can ensure repeatability and consistency of results. The book explains how the lessons learned by studying these individual cases can be applied to a wide range of industries. This work is an ideal resource for undergraduate and postgraduate students, and will also be useful for industry professionals who wish to avoid repeating mistakes that resulted in devastating consequences. * Explores the root cause of disasters and various preventative measures* Links theory with practice in regard to risk, safety, and reliability analyses* Uses analytical techniques originating from reliability analysis of equipment failures, multiple criteria decision making, and artificial intelligence domains

Ashraf Labib is Professor of Operations and Decision Analysis at Portsmouth Business School, and before this was the Associate Dean (Research) of the Business School and Director of the DBA Programme. His main research interest lies in the field of Strategic Operations Management and Decision Analysis, including Manufacturing, Reliability Engineering and Maintenance Systems, Multiple Criteria Decision-Analysis and Applications of Artificial Intelligence such as Fuzzy Logic. Prior to joining Portsmouth Business School, Professor Labib was a Senior Lecturer in the Manufacturing Division of the Department of Mechanical, Aerospace and Manufacturing Engineering at UMIST. He has published 120-refereed papers in professional journals and international conferences proceedings and has attracted research-funded projects from EPSRC, ESRC, European Commission and industry. He have been involved in the design, development, and implementation of Computerised Maintenance Management Systems (CMMSs), Stock Control Spares and Ordering Systems for major companies in the automotive sector such as Land Rover, Rockwell, Peugeot Talbot and Federal Mogul - Ferodo.


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