Dependent, independent, and pseudo-independent protection layers in risk analysis
Risk analysis is an important tool to provide support for various risk management decisions in hazardous industries. For the last decade, the semiquantitative Layers of Protection Analysis (LOPA) has been the dominating risk analysis technique in the US process industry. One basic assumption in LOPA...
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Published in | Process safety progress Vol. 35; no. 3; pp. 286 - 294 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Blackwell Publishing Ltd
01.09.2016
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Online Access | Get full text |
ISSN | 1066-8527 1547-5913 |
DOI | 10.1002/prs.11796 |
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Abstract | Risk analysis is an important tool to provide support for various risk management decisions in hazardous industries. For the last decade, the semiquantitative Layers of Protection Analysis (LOPA) has been the dominating risk analysis technique in the US process industry. One basic assumption in LOPA is that all the protection layers are independent from each other and from the initiating cause; otherwise, no risk reduction credit should be taken in the LOPA. However, many processes do have protection layers, which are dependent to some extent. For these systems, assuming independency may be too optimistic, whereas disregarding the partial risk reduction afforded from a partially dependent protection layer is pessimistic.
This article considers processes with dependent protection layers (with a shared component), independent protection layers, and pseudo‐independent protection layers (subject to common cause failure). A long distance gas pipeline system is used as an example. Using reduced Event Trees for incident scenario modeling, Fault Trees for protection layers, and solving them in a coupled calculation, this article shows how protection layer dependencies are treated in risk analysis to obtain the overall risk reduction without being too optimistic or pessimistic. © 2015 American Institute of Chemical Engineers Process Saf Prog 35: 286–294, 2016 |
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AbstractList | Risk analysis is an important tool to provide support for various risk management decisions in hazardous industries. For the last decade, the semiquantitative Layers of Protection Analysis (LOPA) has been the dominating risk analysis technique in the US process industry. One basic assumption in LOPA is that all the protection layers are independent from each other and from the initiating cause; otherwise, no risk reduction credit should be taken in the LOPA. However, many processes do have protection layers, which are dependent to some extent. For these systems, assuming independency may be too optimistic, whereas disregarding the partial risk reduction afforded from a partially dependent protection layer is pessimistic.
This article considers processes with dependent protection layers (with a shared component), independent protection layers, and pseudo‐independent protection layers (subject to common cause failure). A long distance gas pipeline system is used as an example. Using reduced Event Trees for incident scenario modeling, Fault Trees for protection layers, and solving them in a coupled calculation, this article shows how protection layer dependencies are treated in risk analysis to obtain the overall risk reduction without being too optimistic or pessimistic. © 2015 American Institute of Chemical Engineers Process Saf Prog 35: 286–294, 2016 Risk analysis is an important tool to provide support for various risk management decisions in hazardous industries. For the last decade, the semiquantitative Layers of Protection Analysis (LOPA) has been the dominating risk analysis technique in the US process industry. One basic assumption in LOPA is that all the protection layers are independent from each other and from the initiating cause; otherwise, no risk reduction credit should be taken in the LOPA. However, many processes do have protection layers, which are dependent to some extent. For these systems, assuming independency may be too optimistic, whereas disregarding the partial risk reduction afforded from a partially dependent protection layer is pessimistic. This article considers processes with dependent protection layers (with a shared component), independent protection layers, and pseudo-independent protection layers (subject to common cause failure). A long distance gas pipeline system is used as an example. Using reduced Event Trees for incident scenario modeling, Fault Trees for protection layers, and solving them in a coupled calculation, this article shows how protection layer dependencies are treated in risk analysis to obtain the overall risk reduction without being too optimistic or pessimistic. copyright 2015 American Institute of Chemical Engineers Process Saf Prog 35: 286-294, 2016 |
Author | Summers, Angela Jin, Hui |
Author_xml | – sequence: 1 givenname: Hui surname: Jin fullname: Jin, Hui email: hjin@sis-tech.com organization: SIS-TECH Solutions, LP, 12621 Featherwood Drive, Suite 120, TX, 77034, Houston – sequence: 2 givenname: Angela surname: Summers fullname: Summers, Angela organization: SIS-TECH Solutions, LP, 12621 Featherwood Drive, Suite 120, TX, 77034, Houston |
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References | M. Rausand and A. Høyland, System Reliability Theory; Models, Statistical Methods, and Applications, 2nd Edition, Wiley, Hoboken, NJ, 2004. CCPS, Layer of Protection Analysis: Simplified Process Risk Assessment, Center for Chemical Process Safety, American Institute of Chemical Engineers, New York, NY, 2001. R. Freeman, Quantifying LOPA uncertainty, Process Saf Prog 31 (2012), 240-247. NOG, Guidelines for the Application of IEC 61508 and IEC 61511 in the Petroleum Activities on the Norwegian Continental Shelf, Norwegian Oil Industry Association, Stavanger, Norway, 2004. M. Gentile and A.E. Summers, Random, systematic, and common cause failure: How do you manage them? Process Saf Prog 25 (2006), 331-338. SIS-TECH, SIL Solver 7.0, SIS-TECH Solution, Houston, TX, 2014. Isograph, Reliability Workbench 12.0, Isograph, UK, 2014. IEC, Functional Safety: Safety Instrumented Systems for the Process Industry Sector, Part 1-3, International Electrotechnical Commission, Geneva, 2003. H. Jin, M.A. Lundteigen, and M. Rausand, Uncertainty assessment of reliability estimates for safety-instrumented systems, Proc Inst Mech Eng Part O J Risk Reliab 226 (2012), 646-665. 2004 2003 2014 2001 2012; 226 2012; 31 2006; 25 e_1_2_10_9_1 Isograph (e_1_2_10_7_1) 2014 e_1_2_10_10_1 SIS‐TECH (e_1_2_10_8_1) 2014 CCPS (e_1_2_10_4_1) 2001 IEC (e_1_2_10_3_1) 2003 NOG (e_1_2_10_2_1) 2004 Rausand M. (e_1_2_10_5_1) 2004 e_1_2_10_6_1 |
References_xml | – reference: IEC, Functional Safety: Safety Instrumented Systems for the Process Industry Sector, Part 1-3, International Electrotechnical Commission, Geneva, 2003. – reference: Isograph, Reliability Workbench 12.0, Isograph, UK, 2014. – reference: M. Gentile and A.E. Summers, Random, systematic, and common cause failure: How do you manage them? Process Saf Prog 25 (2006), 331-338. – reference: M. Rausand and A. Høyland, System Reliability Theory; Models, Statistical Methods, and Applications, 2nd Edition, Wiley, Hoboken, NJ, 2004. – reference: H. Jin, M.A. Lundteigen, and M. Rausand, Uncertainty assessment of reliability estimates for safety-instrumented systems, Proc Inst Mech Eng Part O J Risk Reliab 226 (2012), 646-665. – reference: NOG, Guidelines for the Application of IEC 61508 and IEC 61511 in the Petroleum Activities on the Norwegian Continental Shelf, Norwegian Oil Industry Association, Stavanger, Norway, 2004. – reference: SIS-TECH, SIL Solver 7.0, SIS-TECH Solution, Houston, TX, 2014. – reference: CCPS, Layer of Protection Analysis: Simplified Process Risk Assessment, Center for Chemical Process Safety, American Institute of Chemical Engineers, New York, NY, 2001. – reference: R. Freeman, Quantifying LOPA uncertainty, Process Saf Prog 31 (2012), 240-247. – volume: 226 start-page: 646 year: 2012 end-page: 665 article-title: Uncertainty assessment of reliability estimates for safety‐instrumented systems publication-title: Proc Inst Mech Eng Part O J Risk Reliab – year: 2014 – year: 2001 – volume: 31 start-page: 240 year: 2012 end-page: 247 article-title: Quantifying LOPA uncertainty publication-title: Process Saf Prog – year: 2004 – year: 2003 – volume: 25 start-page: 331 year: 2006 end-page: 338 article-title: Random, systematic, and common cause failure: How do you manage them? publication-title: Process Saf Prog – volume-title: System Reliability Theory; Models, Statistical Methods, and Applications year: 2004 ident: e_1_2_10_5_1 – ident: e_1_2_10_6_1 doi: 10.1002/prs.10145 – volume-title: Layer of Protection Analysis: Simplified Process Risk Assessment year: 2001 ident: e_1_2_10_4_1 – ident: e_1_2_10_9_1 doi: 10.1002/prs.11493 – ident: e_1_2_10_10_1 doi: 10.1177/1748006X12462780 – volume-title: Guidelines for the Application of IEC 61508 and IEC 61511 in the Petroleum Activities on the Norwegian Continental Shelf year: 2004 ident: e_1_2_10_2_1 – volume-title: Functional Safety: Safety Instrumented Systems for the Process Industry Sector, Part 1‐3 year: 2003 ident: e_1_2_10_3_1 – volume-title: Reliability Workbench 12.0 year: 2014 ident: e_1_2_10_7_1 – volume-title: SIL Solver 7.0 year: 2014 ident: e_1_2_10_8_1 |
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SubjectTerms | Chemical engineers common cause failure Common cause failures dependent failure Event tree analysis Fault trees Gas pipelines LOPA Reduction Risk Risk analysis |
Title | Dependent, independent, and pseudo-independent protection layers in risk analysis |
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