Research Article
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Year 2022, , 12 - 24, 30.03.2022
https://doi.org/10.54287/gujsa.1074379

Abstract

References

  • AIChE PERD, American Institute of Chemical Engineers (2020, August 27). (Accessed:20/12/2021) www.aiche.org/ccps/resources/process-equipment-reliability-database-perd
  • ASME PCC-3:2007 (2008). Inspection Planning Using Risk-Based Methods. American Society of Mechanical Engineers Standarts.
  • API RP 581:2016 (2016). Risk-based Inspection Methodology (3rd ed.). American Petroleum Institute (API) Standarts.
  • Baybutt, P. (2015). A critique of the Hazard and Operability (HAZOP) study. Journal of Loss Prevention in the Process Industries, 33, 52-58.
  • CCPS, Center for Chemical Process Safety (2014). Guidelines for Initiating Events and Independent Protection Layers in Layer of Protection Analysis. Wiley.
  • DNV-RP-G101 (2002). Risk Based Inspection of Offshore Topsides Static Mechanical Equipment. Det Norske Veritas Standarts.
  • DNV, Det Norske Veritas (2013), Failure Frequency Guidance: Process Equipment Leak Frequency Data for Use in QRA.
  • EN 16991 (2018). Risk-based inspection framework. European Standarts.
  • EEMUA 159 (2017). Above ground flat bottomed storage tanks - a guide to inspection, maintenance and repair. Engineering Equipment and Materials Users Association Publications.
  • EEMUA 206 (2006). A Risk Based Inspection - a guide to effective use of the RBI process. Engineering Equipment and Materials Users Association Publications.
  • IOGP, International Oil & Gas Producers (2019). (Accessed:14/01/2021) www.iogp.org/bookstore/product/ risk-assessment-data-directory-process-release-frequencies
  • Keeley, D., Turner, S., & Harper, P. (2011). Management of the UK HSE failure rate and event data. Journal of Loss Prevention in the Process Industries, 24(3), 237-241. doi:10.1016/j.jlp.2010.09.002
  • Pittiglio, P., Bragatto, P., & Site, C. D. (2014). Updated failure rates and risk management in process industries. Energy Procedia, 45, 1364-1371. doi:10.1016/j.egypro.2014.01.143
  • CPR 18E (2005). Guidelines for quantitative risk assessment ‘Purple Book’. Publication Series on Dangerous Substances (PSG3). Netherlands Ministry of Housing, Spatial Planning and the Environment.
  • Revie R. W. (2015). Oil and Gas Pipelines Integrity and Safety Handbook. John Wiley & Sons, Inc.
  • Wood, M. H., Vetere Arellano, A. L., & Van Wijk, L. (2013). Lessons learned from accidents in EU and OECD countries, Corrosion‐Related Accidents in Petroleum Refineries, The European Commission's science and knowledge service. doi:10.2788/37964
  • URL1, (2019, March 02). Regulation on prevention of major industrial accidents and lessening their adverse impacts “Büyük Endüstriyel Kazaların Önlenmesi ve Etkilerinin Azaltılması Hakkında Yönetmelik”. Official Gazette of the Republic of Turkey, No:30702. www.resmigazete.gov.tr/eskiler/2019/03/20190302-1.htm

Effect of Equipment Component Generic Frequency Data on Probability of Failure Calculations for Risk-Based Inspection

Year 2022, , 12 - 24, 30.03.2022
https://doi.org/10.54287/gujsa.1074379

Abstract

A software was developed to use equipment component frequency data specific to the facility or provided from different sources in lost event probability calculations for risk-based inspection. Corrosion causes equipment aging and loss events in which hazardous substances are released uncontrollably. The API RP 581 Recommended Practise of the American Petroleum Institute is widely used in the calculation of corrosion-based loss event risks for static pressure equipment such as atmospheric tanks, heat exchangers, columns, reactors, and used for basis of the developed software. In API RP 581, the risk of loss event is defined as the product of the probability of failure and the severity of consequence. Equipment component generic failure frequencies are a variable at the probability of failure calculation. Current software use only equipment component generic failure frequencies given at API RP 581. For this reason, establishment-specific equipment component failure frequency data or data that can be obtained from other sources cannot be used. To solve this problem, a software based on API RP 581 methodology has been developed and provided with the opportunity for the user to enter equipment component failure frequency data from different sources. The findings showed that when using data from different literature sources, there are different results up to 1491% in the probability of failures. Since the increase in the probability of the failures will increase the risk, that creates results such as pulling the equipment inspection dates forward, performing more effective and therefore more costly inspections, increasing the precautions and costs to be taken. Therefore, software which are based on API RP 581 methodology should be developed in such a way that different generic frequency data can be used.

References

  • AIChE PERD, American Institute of Chemical Engineers (2020, August 27). (Accessed:20/12/2021) www.aiche.org/ccps/resources/process-equipment-reliability-database-perd
  • ASME PCC-3:2007 (2008). Inspection Planning Using Risk-Based Methods. American Society of Mechanical Engineers Standarts.
  • API RP 581:2016 (2016). Risk-based Inspection Methodology (3rd ed.). American Petroleum Institute (API) Standarts.
  • Baybutt, P. (2015). A critique of the Hazard and Operability (HAZOP) study. Journal of Loss Prevention in the Process Industries, 33, 52-58.
  • CCPS, Center for Chemical Process Safety (2014). Guidelines for Initiating Events and Independent Protection Layers in Layer of Protection Analysis. Wiley.
  • DNV-RP-G101 (2002). Risk Based Inspection of Offshore Topsides Static Mechanical Equipment. Det Norske Veritas Standarts.
  • DNV, Det Norske Veritas (2013), Failure Frequency Guidance: Process Equipment Leak Frequency Data for Use in QRA.
  • EN 16991 (2018). Risk-based inspection framework. European Standarts.
  • EEMUA 159 (2017). Above ground flat bottomed storage tanks - a guide to inspection, maintenance and repair. Engineering Equipment and Materials Users Association Publications.
  • EEMUA 206 (2006). A Risk Based Inspection - a guide to effective use of the RBI process. Engineering Equipment and Materials Users Association Publications.
  • IOGP, International Oil & Gas Producers (2019). (Accessed:14/01/2021) www.iogp.org/bookstore/product/ risk-assessment-data-directory-process-release-frequencies
  • Keeley, D., Turner, S., & Harper, P. (2011). Management of the UK HSE failure rate and event data. Journal of Loss Prevention in the Process Industries, 24(3), 237-241. doi:10.1016/j.jlp.2010.09.002
  • Pittiglio, P., Bragatto, P., & Site, C. D. (2014). Updated failure rates and risk management in process industries. Energy Procedia, 45, 1364-1371. doi:10.1016/j.egypro.2014.01.143
  • CPR 18E (2005). Guidelines for quantitative risk assessment ‘Purple Book’. Publication Series on Dangerous Substances (PSG3). Netherlands Ministry of Housing, Spatial Planning and the Environment.
  • Revie R. W. (2015). Oil and Gas Pipelines Integrity and Safety Handbook. John Wiley & Sons, Inc.
  • Wood, M. H., Vetere Arellano, A. L., & Van Wijk, L. (2013). Lessons learned from accidents in EU and OECD countries, Corrosion‐Related Accidents in Petroleum Refineries, The European Commission's science and knowledge service. doi:10.2788/37964
  • URL1, (2019, March 02). Regulation on prevention of major industrial accidents and lessening their adverse impacts “Büyük Endüstriyel Kazaların Önlenmesi ve Etkilerinin Azaltılması Hakkında Yönetmelik”. Official Gazette of the Republic of Turkey, No:30702. www.resmigazete.gov.tr/eskiler/2019/03/20190302-1.htm
There are 17 citations in total.

Details

Primary Language English
Journal Section Chemical Engineering
Authors

İbrahim Tükenmez 0000-0003-3669-2160

Hüseyin Baran Akinbingöl 0000-0002-4020-6359

Publication Date March 30, 2022
Submission Date February 16, 2022
Published in Issue Year 2022

Cite

APA Tükenmez, İ., & Akinbingöl, H. B. (2022). Effect of Equipment Component Generic Frequency Data on Probability of Failure Calculations for Risk-Based Inspection. Gazi University Journal of Science Part A: Engineering and Innovation, 9(1), 12-24. https://doi.org/10.54287/gujsa.1074379