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Propose a practical plan for the identification of Safety‐Critical Equipment.

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Title: Propose a practical plan for the identification of Safety‐Critical Equipment.
Authors: Lu, Yen‐Ju1 (AUTHOR), Lin, Rong‐Zan1 (AUTHOR), Wang, Chen‐Hua1 (AUTHOR) cwang@nkust.edu.tw
Source: Process Safety Progress. Mar2025, Vol. 44 Issue 1, p39-48. 10p.
Subjects: Technological risk assessment, Occupational hazards, Chemical processes, Petroleum chemicals industry, Chemical industry
Abstract: The petrochemical and chemical industries are widely regarded as process industries with significant hazards. Investigations of numerous accidents have shown that over half are caused by equipment failures. Proper management of Safety‐Critical Equipment (SCE) related to major hazards and ensuring their functional integrity can significantly reduce the occurrence of Process Safety Management (PSM) accidents. There are currently many risk assessment technologies available to provide a foundational basis for SCE identification, although each method has its limitations. In 2016, the Center for Chemical Process Safety (CCPS) published guidelines for asset integrity (CCPS, 2017), outlining the process for determining SCE, offering a practical identification approach to the industry. However, the principles of this method are broad, and its practical implementation remains unclear. Therefore, this paper discusses how to integrate various risk assessment methods and develop a feasible procedure for SCE identification in practice. It highlights the need to link identified SCEs to corresponding safety‐critical tasks to ensure the functional integrity of the equipment. [ABSTRACT FROM AUTHOR]
Copyright of Process Safety Progress is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="AR" term="%22Lu%2C+Yen‐Ju%22">Lu, Yen‐Ju</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lin%2C+Rong‐Zan%22">Lin, Rong‐Zan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Chen‐Hua%22">Wang, Chen‐Hua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> cwang@nkust.edu.tw</i>
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  Data: <searchLink fieldCode="JN" term="%22Process+Safety+Progress%22">Process Safety Progress</searchLink>. Mar2025, Vol. 44 Issue 1, p39-48. 10p.
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  Data: The petrochemical and chemical industries are widely regarded as process industries with significant hazards. Investigations of numerous accidents have shown that over half are caused by equipment failures. Proper management of Safety‐Critical Equipment (SCE) related to major hazards and ensuring their functional integrity can significantly reduce the occurrence of Process Safety Management (PSM) accidents. There are currently many risk assessment technologies available to provide a foundational basis for SCE identification, although each method has its limitations. In 2016, the Center for Chemical Process Safety (CCPS) published guidelines for asset integrity (CCPS, 2017), outlining the process for determining SCE, offering a practical identification approach to the industry. However, the principles of this method are broad, and its practical implementation remains unclear. Therefore, this paper discusses how to integrate various risk assessment methods and develop a feasible procedure for SCE identification in practice. It highlights the need to link identified SCEs to corresponding safety‐critical tasks to ensure the functional integrity of the equipment. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Process Safety Progress is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Mar2025
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