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    What Goes Up, Shouldn't Come Down: Learning from Construction and Engineering Failures

    216730_216730.pdf (234.1Kb)
    Access Status
    Open access
    Authors
    Love, Peter
    Lopez, Robert
    Goh, Yang Miang
    Tam, C.
    Date
    2011
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Love, P. and Lopez, R. and Goh, Y. and Tam, C. 2011. What Goes Up, Shouldn't Come Down: Learning from Construction and Engineering Failures, in Proceedings of the Twelfth East Asia-Pacific Conference on Structural Engineering and Construction - EASEC12. Procedia Engineering. 14: pp. 844-850.
    Source Title
    Procedia Engineering 14 The Proceedings of the Twelfth East Asia-Pacific Conference on Structural Engineering and Construction EASEC12
    Source Conference
    EASEC-12
    DOI
    10.1016/j.proeng.2011.07.107
    ISSN
    1877-7058
    School
    School of Built Environment
    Remarks

    This open access article is distributed under the Creative Commons license http://creativecommons.org/licenses/by-nc-nd/3.0/

    URI
    http://hdl.handle.net/20.500.11937/26400
    Collection
    • Curtin Research Publications
    Abstract

    Design errors can severely jeopardize safety and contribute to failures in construction and engineering projects. Such failures can have devastating economic, environmental and social consequences. Significant efforts have been made to reduce the incidence of failures through learning from previous disasters and events by modifying building and engineering codes and standards accordingly. Design errors, however, remain an innate feature of construction and engineering projects. Most errors are identified during construction and require rework, but there is always a potential for some to remain undetected and contribute to failure, and as a result potentially contribute to accidents and loss of life. This paper examines the circumstances and issues that contributed to a series of construction and engineering failures, to enable development of a systemic learning framework to contain and reduce design errors and potential failures and accidents.

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