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Learning from failures : decision analysis of major disasters / Ashraf Labib.

By:

Labib, Ashraf

Material type: Text

TextPublication details: Amsterdam ; Boston : Elsevier Butterworth-Heinemann, 2014.Edition: First editionDescription: xi, 321 pages : illustrations ; 25 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780124167278 (hardcover)

Subject(s):

Genre/Form:

Case studies.

DDC classification:

658.4/056 23

LOC classification:

HD49 .L33 2014

Summary: 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 mo.

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Holdings
Item type	Current library	Call number	Status	Barcode
Books	Kwara State University Library	HD49 .L33 2014 (Browse shelf(Opens below))	Available	014969-01
Books	Kwara State University Library	HD49 .L33 2014 (Browse shelf(Opens below))	Available	014969-02
Books	Kwara State University Library	HD49 .L33 2014 (Browse shelf(Opens below))	Available	014969-03

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Includes bibliographical references (pages 285-308) and index.

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 mo.

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