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    4. Operational Risks Evaluation in Cement Industry using Bayesian Network with Uncertainty
    Risk Assessment and Occupational Health and Safety (OHS)

    Operational Risks Evaluation in Cement Industry using Bayesian Network with Uncertainty

    200 views 18 Downloads
    PM
    Pham Ngoc Xuan Mai International University – Vietnam National University - HCMC
    VY
    Vincent Yu National Taiwan University of Science and Technology
    QP
    Quang Pham Ngoc National Taiwan University of Science and Technology
    PA
    Pham Tuan Anh National Taiwan University of Science and Techonology
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    In order to ensure a successful cement manufacturing process and avoid negative consequences, it is crucial to identify and analyze potential risks. The aim of this research paper is to use two models, the Fault Tree analysis and Bayesian Networks, to identify and mitigate risks associated with the process. While both models are useful, the Bayesian Network model is the dominant one used in the research, and it has been combined with the Fault Tree model to address its limitations. Together, the two models work to produce the best possible outcome in terms of risk identification and mitigation. The paper intends to offer a solution to evaluate risk profiles in the cement industry using Bayesian models. The goal is to improve the methodologies of identifying risk events and categories by examining them under uncertainty. The results obtained from this research will help managers make better decisions by considering the significance of confidence intervals within the uncertainty region. This approach will ensure that the process is well-planned and that risks are identified and mitigated to avoid negative consequences, such as worker injuries and harm to third-party personnel.    


    Published in 6th European International Conference on Industrial Engineering and Operations Management, Lisbon, Portugal
    Publisher IEOM Society International
    Date of Conferences July 18–20, 2023
    DOI 10.46254/EU6.20230093
    ISBN 979-8-3507-0547-8
    ISSN/E-ISSN 2169-8767

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