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- W4387230105 abstract "Abstract As society and the economy gravitates toward cleaner and renewable energy, the energy sector continues to diversify and increase in complexity, leading to a ‘never normal’ business portfolio and project delivery. On top of safeguarding On Time, On Budget, and On Scope delivery, this constant state of change also warrants new ways of managing Health, Safety and Environment (HSE). At PETRONAS, new ways of working is synonymous with digital transformation. Hence, this paper will outline how PETRONAS leverages digital technologies in managing HSE risks in project delivery. Since 2019, the project delivery arm of PETRONAS has invested in developing an artificial intelligence (AI) predictive model to predict future HSE risks and incidents based on historical HSE incident big data. Coupled with real-time data visualization and prescription of control measures, this digital solution has greatly enabled the organization to rationalize resources and implement informed, risk-based interventions. Considerable efforts have been made to operationalize the predictive tool, which includes stakeholder management, change management, as well as work process enhancement to incorporate automation and have end-to-end oversight on risk mitigation and intervention. This provides a HSE management framework that focuses on data-driven decision-making, which translates to targeted intervention with pace. As a result, PETRONAS project delivery arm has seen incident reduction of more than 55% for both injurious and non-injurious incidents in 2022 in comparison to the preceding three-year average. In addition, the implementation of the digital solution has enabled an improved process cycle efficiency of HSE risk management from 32% to 97%, with a reduction of total mantime of 143 hours." @default.
- W4387230105 created "2023-10-02" @default.
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- W4387230105 date "2023-10-02" @default.
- W4387230105 modified "2023-10-16" @default.
- W4387230105 title "Moving Towards Automation and Artificial Intelligence in Managing HSE Risks and Incidents" @default.
- W4387230105 cites W183625566 @default.
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- W4387230105 doi "https://doi.org/10.2118/216290-ms" @default.
- W4387230105 hasPublicationYear "2023" @default.
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