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    Chapter Safety Training for Rigging Using Virtual Reality

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    Author(s)
    Lemouchi, Rafik
    Assaf, Mohamed
    Al-Hussein, Mohamed
    Boutouhami, Khaoula
    Bouferguene, Ahmed
    Language
    English
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    Abstract
    Tower and Mobile Cranes are some of the most commonly used heavy equipment in all construction sites, and any crane failures could lead to significant human and monetary losses. Moreover, rigging configuration determination is a critical task that requires the rigging crew to have significant experience and knowledge of various failure modes that can be encountered when performing lifting operations. However, despite the criticality of training riggers, there has yet to be a comprehensive tool used to train and guide inexperienced riggers, and hence, more practical tools are needed. This paper proposes a framework for using Virtual reality (VR) and simulation to train riggers to identify the optimal rigging configurations based on the lift type and the external conditions. Through 3D modeling, the critical components of the rigging system are modeled to accurately simulate the rigging system and their performance when faced with critical loading scenarios. The developed framework is expected to allow inexperienced riggers to identify critical failure modes and enhance construction operations' overall safety performance and productivity. Furthermore, several scenarios are assessed based on historical evidence for rigging configuration failures, and the efficiency of the training tool is assessed through real-life scenarios and tests
    URI
    https://library.oapen.org/handle/20.500.12657/89114
    Keywords
    Crane Operations; Lift Planning; Rigging; Safety; Training; Virtual Reality
    DOI
    10.36253/979-12-215-0289-3.18
    ISBN
    9791221502893, 9791221502893
    Publisher
    Firenze University Press
    Publisher website
    https://www.fupress.com/
    Publication date and place
    Florence, 2023
    Series
    Proceedings e report, 137
    Classification
    Virtualization
    Pages
    11
    Rights
    https://creativecommons.org/licenses/by-nc/4.0/legalcode
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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