해양환경안전학회지 (Journal of the Korean Society of Marine Environment & Safety)

  • 제29권2호
  • /
  • Pages.238-247
  • /
  • 2023
  • /
  • 1229-3431(pISSN)
  • /
  • 2287-3341(eISSN)
해양환경안전학회 (The Korean Society of Marine Environment and safety)
권호 표지
DOI QR코드

DOI QR Code

퍼지 다기준 HAZOP 기법을 이용한 해상용 LPG 엔진의 위험성 평가

Risk Assessment of Marine LPG Engine Using Fuzzy Multicriteria HAZOP Technique

  • 여실중 (해양수산부 부산지방해양수산청)
  • Siljung Yeo (Busan Regional Office of Ministry of Oceans and Fisheries)
  • 투고 : 2023.03.10
  • 심사 : 2023.04.27
  • 발행 : 2023.04.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

선박 연료로서 LPG는 현재의 기술과 경제성 등을 고려하였을 때 매력적인 연료이다. 하지만, 아직 LPG 연료 선박의 안전 지침을 개발 중에 있고, 국내에서는 중소형 선박에 LPG 추진 시스템을 적용한 사례가 없다. 본 연구에서는 국내 최초 개발된 해상용 LPG 엔진 시스템에 대해 보다 객관적인 위험성 평가를 수행하고 안전 운용 기준을 제안하고자 한다. 우선, 위험과 운전 분석 기법을 통해 동 엔진 시스템을 5개의 검토 구간으로 분할하고 총 58가지의 위험요소를 식별하였다. 그다음 정성적 평가인 HAZOP 기법의 주관성을 보완하기 위해 퍼지 이론을 사용하고 검출도, 민감도 등 위험 요인을 추가하여 퍼지 분석적 계층 과정을 통해 위험 요인의 상대적 가중치를 비교하였다. 그 결과, 5가지의 위험 요인 중, 위험성에 가장 큰 영향을 미치는 위험 요인은 발생 빈도와 심각도로 평가되었다. 마지막으로, 위험 요인에 대한 가중치를 고려하여 위험 순위를 세밀하게 선정하기 위해 퍼지 TOPSIS 기법을 적용하였다. 그 결과, 위험 등급은 47개 그룹으로 구분할 수 있었고, 동 엔진 시스템의 운용 중 가장 위험도가 높은 위험요소는 LPG 공급 라인 유지 보수 중 가스 누출로 분석되었다. 본 연구에 제안된 기법을 LPG 공급계통 등 다양한 설비에도 적용하여, 향후 LPG 추진 선박의 안전 기준 마련을 위한 위험성 평가의 표준절차로 활용할 수 있기를 기대한다.

Liquefied petroleum gas (LPG) is an attractive fuel for ships considering its current technology and economic viability. However, safety guidelines for LPG-fueled ships are still under development, and there have been no cases of applying LPG propulsion systems to small and medium-sized ships in Korea. The purpose of this study was to perform an objective risk assessment for the first marine LPG engine system and propose safe operational standards. First, hazard and operability (HAZOP) analysis was used to divide the engine system into five nodes, and 58 hazards were identified. To compensate for the subjectivity of qualitative evaluation using HAZOP analysis, fuzzy set theory was used, and additional risk factors, such as detectability and sensitivity, were included to compare the relative weights of the risk factors using a fuzzy analytical hierarchy process. As a result, among the five risk factors, those with a major impact on risk were determined to be the frequency and severity. Finally, the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the risk rank more precisely by considering the weights of the risk factors. The risk level was divided into 47 groups, and the major hazard during the operation of the engine system was found through the analysis to be gas leakage during maintenance of the LPG supply line. The technique proposed can be applied to various facilities, such as LPG supply systems, and can be utilized as a standard procedure for risk assessment in developing safety standards for LPG-powered ships.

키워드

참고문헌

  1. Ahn, J. and D. Chang(2016), Fuzzy-based HAZOP study for process industry, J. Hazard. Mater., 317, pp. 303-311. https://doi.org/10.1016/j.jhazmat.2016.05.096
  2. Ampah, J.D., Yusuf, A.A., Afrane, S., Jin, C., Liu, H.(2021), Reviewing two decades of cleaner alternative marine fuels: towards IMO's decarbonization of the maritime transport sector, J. Clean. Prod., 320, pp. 128871.
  3. Aras, F., E. Karakas, and Y. Bicen(2014), Fuzzy logic-based user interface design for risk assessment considering human factor: a case study for high-voltage cell, Saf. Sci., 70, pp. 387-396. https://doi.org/10.1016/j.ssci.2014.07.013
  4. Cao, Y., Q. J. Jia, S. M. Wang, Y. Jiang, and Y. Bai(2022), Safety design analysis of a vent mast on a LNG powered ship during a low-temperature combustible gas leakage accident, J. Ocean Eng. Sci., 7(1), pp. 75-83. https://doi.org/10.1016/j.joes.2021.06.001
  5. Carpitella, S., A. Certa, J. Izquierdo, and C. M. La Fata (2018), A combined multi-criteria approach to support FMECA analyses: a real-world case, Reliab. Eng. Syst. Saf., 169, pp. 394-402. https://doi.org/10.1016/j.ress.2017.09.017
  6. Chang, D. -Y.(1996), Applications of the extent analysis method on fuzzy AHP, Eur. J. Oper. Res., 95(3), pp. 649-655. https://doi.org/10.1016/0377-2217(95)00300-2
  7. Chen, C. T.(2000), Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114(1), pp. 1-9. https://doi.org/10.1016/S0165-0114(97)00377-1
  8. Cheraghi, M., A. E. Baladeh, and N. Khakzad(2019), A fuzzy multi-attribute HAZOP technique (FMA-HAZOP): Application to gas wellhead facilities, Safety science, 114, pp. 12-22. https://doi.org/10.1016/j.ssci.2018.12.024
  9. DNV(2017), LPG as a Marine Fuel, p. 21.
  10. Grassi, A., R. Gamberini, C. Mora, and B. Rimini(2009), A fuzzy multi-attribute model for risk evaluation in workplaces, Saf. Sci., 47(5), pp. 707-716. https://doi.org/10.1016/j.ssci.2008.10.002
  11. IEC:61882(2001), Hazard and Operability Studies (HAZOP Studies) - Application Guide, International Electrotechnical Commission.
  12. ISO(2009), "IRisk management - Risk assessment techniques", British standard, pp. 50-52.
  13. Lees, F.(2012), Lees' Loss Prevention in the Process Industries: Hazard Identification, Assessment and Control, Butterworth-Heinemann.
  14. Monzingo, D. G.(2020), The Propane-Fueled Ship, In SNAME Maritime Convention, OnePetro, p. 8.
  15. O Herrera, M. A. de la, A. S. Luna, A. C. A. da Costa, E. M. B. Lemes(2018), Risk Analysis: A generalized Hazop methodology state-of-the-art, applications, and perspective in the process industry. Vigilancia Sanitaria em Debate: Sociedade, Ciencia & Tecnologia, 6(2), pp. 106-121. https://doi.org/10.22239/2317-269x.00990
  16. Pinto, A.(2014), QRAM a qualitative occupational safety risk assessment model for the construction industry that incorporate uncertainties by the use of fuzzy sets, Saf. Sci., 63, pp. 57-76. https://doi.org/10.1016/j.ssci.2013.10.019
  17. Raviv, G., A. Shapira, and B. Fishbain(2017), AHP-based analysis of the risk potential of safety incidents: case study of cranes in the construction industry, Saf. Sci., 91, pp. 298-309. https://doi.org/10.1016/j.ssci.2016.08.027
  18. Saaty, T. L.(1980), The Analytic Hierarchy Process, Mac Graw-Hill, New York.
  19. Salih, M. M., B. B. Zaidan, A. A. Zaidan, M. A. Ahmed(2019), Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017, Computers & Operations Research, 104, pp. 207-227. https://doi.org/10.1016/j.cor.2018.12.019
  20. Vahidnia, M. H., A. A. Alesheikh, and A. Alimohammadi (2009), Hospital site selection using fuzzy AHP and its derivatives, J. Environ. Manage., 90(10), pp. 3048-3056. https://doi.org/10.1016/j.jenvman.2009.04.010
  21. Xing, H., C. Stuart, S. Spence, and H. Chen(2021), Alternative fuel options for low carbon maritime transportation: Pathways to 2050, J. Clean. Prod., 297, 126651.
  22. Yeo, S. J., J. Kim, and W. J. Lee(2022), Potential economic and environmental advantages of liquid petroleum gas as a marine fuel through analysis of registered ships in South Korea, J. Clean. Prod., Vol. 330, 129955.
  23. Yeo, S., B. Jeong, and W. J. Lee(2023), Improved formal safety assessment methodology using fuzzy TOPSIS for LPG-fueled marine engine system. Ocean Engineering, Vol. 269, 113536.
  24. Zimmermann, H. J.(2011), Fuzzy Set Theory - And Its Applications, Springer Science & Business Media.