Risk Assessment and Occupational Health and Safety (OHS)

Operational Risks Evaluation in Cement Industry using Bayesian Network with Uncertainty

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SA

Save Akilimalissiga University of Johannesburg

NS

Nita Sukdeo University of Johannesburg

SM

Sambil Charles Mukwakungu University of Johannesburg

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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