Skip to main content
SpringerLink
Log in

Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA

  • Original Research Article
  • Published:
Journal of Failure Analysis and Prevention Aims and scope Submit manuscript

Abstract

Applying the fuzzy logic method to FMEA and its correlation with performance investigations is rarely applied in analyzing refrigeration system risk. The aim of this study is investigate the refrigeration system performance and analyze the risk of failure mode in the performance of the refrigeration system using the fuzzy-FMEA method. In calculating performance, the COP parameter is needed. Prioritization of failure modes uses conventional FMEA (C-FMEA) and fuzzy-based FMEA (Fuzzy-FMEA), which produces conventional RPN (C-RPN) and fuzzy-RPN (F-RPN). Pareto diagrams are used to classify RPN categories which are the main causes. The result of the study is that the calculation of the refrigeration system performance shows a decreasing trend with increasing operating time. In the risk analysis, it was found that the F21 (evaporator) failure has the same rating, and the highest is C-RPN (252) and F-RPN (750). Five categories need to be mitigated. The application of fuzzy-FMEA determines the critical failure priority of the evaporator. The results of this study provide new insights into developing engine performance investigations by determining critical failure modes to get mitigation quickly by minimizing expert opinion expertise.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9.
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. L. Franceschelli, A. Berardinelli, S. Dabbou, L. Ragni, M. Tartagni, Sensing technology for fish freshness and safety: a review. Sensors. 21, 1–24 (2021)

    Article  Google Scholar 

  2. A.C. Yilmaz, Performance evaluation of a refrigeration system using nanolubricant. Appl. Nanosci.Nanosci. 10, 1667–1678 (2020)

    Article  CAS  Google Scholar 

  3. J. Balaraju, M. Govinda Raj, C.S. Murthy, Fuzzy-FMEA risk evaluation approach for LHD machine-A case study. J. Sustain. Min. 18, 257–268 (2019)

    Article  Google Scholar 

  4. I. Alsyouf, The role of maintenance in improving companies’ productivity and profitability. Int. J. Prod. Econ. 105, 70–78 (2007)

    Article  Google Scholar 

  5. Y. Wang, G. Cheng, H. Hu, W. Wu, Development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant. J. Loss Prev. Process Ind. 25, 958–965 (2012)

    Article  CAS  Google Scholar 

  6. J.S. Tan, M.A. Kramer, A general framework for preventive maintenance optimization in chemical process operations. Comput. Chem. Engng. 21, 1451–1469 (1997)

    Article  CAS  Google Scholar 

  7. F. Backlund, J. Hannu, Can we make maintenance decisions on risk analysis results? J. Qual. Maint. Eng.Maint. Eng. 8, 77–91 (2002)

    Article  Google Scholar 

  8. S. Baldi, T. Le Quang, O. Holub, P. Endel, Real-time monitoring energy efficiency and performance degradation of condensing boilers. Energy Convers. Manag. 136, 329–339 (2017)

    Article  Google Scholar 

  9. G. Bogdanovská, V. Molnár, G. Fedorko, Failure analysis of condensing units for refrigerators with refrigerant R134a, R404A. Int. J. Refrig.Refrig. 100, 208–219 (2019)

    Article  Google Scholar 

  10. K. Chandra, V. Kain, P.S. Shetty, R. Kishan, Failure analysis of copper tube used in a refrigerating plant. Eng. Fail. Anal. 37, 1–11 (2014)

    Article  CAS  Google Scholar 

  11. H. Arabian-Hoseynabadi, H. Oraee, P.J. Tavner, Failure modes and effects analysis (FMEA) for wind turbines. Int. J. Electr. Power Energy Syst. Electr. Power Energy Syst. 32, 817–824 (2010)

    Article  Google Scholar 

  12. A. Jomde, V. Bhojwani, S. Kedia, N. Jangale, K. Kolas, P. Khedkar, S. Deshmukh, Failure modes effects and criticality analysis of the linear compressor. Mater. Today: Proc. 4(9), 10184–10188 (2017). https://doi.org/10.1016/j.matpr.2017.06.345

    Article  Google Scholar 

  13. K.P. Lijesh, S.M. Muzakkir, H. Hirani, Failure mode and effect analysis of passive magnetic bearing. Eng. Fail. Anal. 62, 1–20 (2016)

    Article  Google Scholar 

  14. E. Adar, M. Ince, B. Karatop, M.S. Bilgili, The risk analysis by failure mode and effect analysis (FMEA) and fuzzy-FMEA of supercritical water gasification system used in the sewage sludge treatment. J. Environ. Chem. Eng. 5, 1261–1268 (2017)

    Article  CAS  Google Scholar 

  15. H. Li, H. Díaz, C. GuedesSoares, A failure analysis of floating offshore wind turbines using AHP-FMEA methodology. Ocean Eng. 234, 109261 (2021)

    Article  Google Scholar 

  16. A. Mariajayaprakash, T. Senthilvelan, Failure detection and optimization of sugar mill boiler using FMEA and Taguchi method. Eng. Fail. Anal. 30, 17–26 (2013)

    Article  Google Scholar 

  17. J.F.W. Peeters, R.J.I. Basten, T. Tinga, Improving failure analysis efficiency by combining FTA and FMEA in a recursive manner. Reliab. Eng. Syst. Saf.. Eng. Syst. Saf. 172, 36–44 (2018)

    Article  Google Scholar 

  18. J.R. Ribas, J.C.R. Severo, L.F. Guimarães, K.P.C. Perpetuo, A fuzzy FMEA assessment of hydroelectric earth dam failure modes: a case study in Central Brazil. Energy Rep. 7, 4412–4424 (2021)

    Article  Google Scholar 

  19. D.V. Petrović, M. Tanasijević, V. Milić, N. Lilić, S. Stojadinović, I. Svrkota, Risk assessment model of mining equipment failure based on fuzzy logic. Expert Syst. Appl. 41, 8157–8164 (2014)

    Article  Google Scholar 

  20. K. Xu, L.C. Tang, M. Xie, S.L. Ho, M.L. Zhu, Fuzzy assessment of FMEA for engine systems. Reliab. Eng. Syst. Saf. Eng. Syst. Saf. 75, 17–29 (2002)

    Article  Google Scholar 

  21. R. Yahmadi, K. Brik, F. Ben Ammar, Fuzzy risk priority number assessment for solar gel battery manufacturing defects. Eng. Fail. Anal. 124, 105327 (2021)

    Article  Google Scholar 

  22. Z. Yang, J. Wang, Use of fuzzy risk assessment in FMEA of offshore engineering systems. Ocean Eng. 95, 195–204 (2015)

    Article  Google Scholar 

  23. H. Gargama, S.K. Chaturvedi, Criticality assessment models for failure mode effects and criticality analysis using fuzzy logic. IEEE Trans. Reliab.Reliab. 60, 102–110 (2011)

    Article  Google Scholar 

  24. G.A. Keskin, C. Özkan, An alternative evaluation of FMEA: fuzzy ART algorithm. Qual. Reliab. Eng. Int.Reliab. Eng. Int. 25, 647–661 (2009)

    Article  Google Scholar 

  25. S.S. Baakeem, J. Orfi, A. Alabdulkarem, Optimization of a multistage vapor-compression refrigeration system for various refrigerants. Appl. Therm. Eng. 136, 84–96 (2018)

    Article  Google Scholar 

  26. M. H. A. Baig, S. G. Prasanthi, (2013) Failure modes and effect analysis of a mechanical assembly by using Mil-Std 1629a Method. Int. J. Adv. Inform. Sci. Technol. (IJAIST) 13: 2.

  27. R. Rakesh, B.C. Jos, G. Mathew, FMEA analysis for reducing breakdowns of a sub system in the life care product manufacturing industry. Int. J. Eng. Sci. Innov. Technol. (IJESIT). 2, 218–225 (2013)

    Google Scholar 

  28. R. Bubbico, S. Di Cave, B. Mazzarotta, Risk analysis for road and rail transport of hazardous materials: a simplified approach. J. Loss Prev. Process Ind. 17, 477–482 (2004)

    Article  Google Scholar 

  29. R. Khasha, M.M. Sepehri, T. Khatibi, A fuzzy FMEA approach to prioritizing surgical cancellation factors. Int J Hosp Res. 2, 17–24 (2013)

    Google Scholar 

  30. J. Yang, H.Z. Huang, L.P. He, S.P. Zhu, D. Wen, Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster-Shafer evidence theory under uncertainty. Eng. Fail. Anal. 18, 2084–2092 (2011)

    Article  Google Scholar 

  31. C. Dağsuyu, E. Göçmen, M. Narlı, A. Kokangül, Classical and fuzzy FMEA risk analysis in a sterilization unit. Comput. Ind. Eng.. Ind. Eng. 101, 286–294 (2016)

    Article  Google Scholar 

  32. K.M. Tay, C.P. Lim, Fuzzy FMEA with a guided rules reduction system for prioritization of failures. Int. J. Quality Reliab. Manage. 23, 1047–1066 (2006)

    Article  Google Scholar 

  33. D.V. Petrović, M. Tanasijević, S. Stojadinović, J. Ivaz, P. Stojković, Fuzzy model for risk assessment of machinery failures. Symmetry. 12, 525 (2020)

    Article  Google Scholar 

  34. R.K. Sharma, D. Kumar, P. Kumar, Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. Int. J. Quality Reliab. Manage. 22, 986–1004 (2005)

    Article  Google Scholar 

  35. C.W. Nugroho, T. Pitana, B. Dinariyana, Risk analysis using job safety analysis-fuzzy integration for ship maintenance operation. IPTEK J. Technol. Sci. 31, 327 (2020)

    Article  Google Scholar 

  36. J. Kaur, R. Sidhu, A. Awasthi, S.K. Srivastava, A Pareto investigation on critical barriers in green supply chain management. Int. J. Manage. Sci. Eng. Manage. 14, 113–123 (2019)

    Google Scholar 

  37. H.R. Feili, N. Akar, H. Lotfizadeh, M. Bairampour, S. Nasiri, Risk analysis of geothermal power plants using failure modes and effects analysis (FMEA) technique. Energy Convers. Manag. 72, 69–76 (2013)

    Article  Google Scholar 

  38. Q. Wang, T. Li, Y. Jia, W. Zhang, Thermodynamic performance comparison of series and parallel two-stage evaporation vapor compression refrigeration cycle. Energy Rep. 7, 1616–1626 (2021)

    Article  Google Scholar 

  39. K. Arumuganainar, M. Edwin, J.B. Raj, Investigation on the performance improvement of household refrigeration system using R-134a refrigerant blended with ceria nano additives. Appl. Nanosci.Nanosci. 12, 1753–1761 (2022)

    Article  CAS  Google Scholar 

  40. M.R. Braun, P. Walton, S.B.M. Beck, Illustrating the relationship between the coefficient of performance and the coefficient of system performance by means of an R404 supermarket refrigeration system. Int. J. Refrig.Refrig. 70, 225–234 (2016)

    Article  CAS  Google Scholar 

  41. S.M. Ch, N. Ch, D. Samal, S. Kumar, P. Garre, A. Review, Increase in performance of vapour compression refrigeration system using fan. Int. J. Eng. Appl. Sci. (IJEAS). 2, 12–14 (2015)

    Google Scholar 

  42. M.C. Constantino, F.T. Kanizawa, Evaluation of pressure drop effect on COP of single-stage vapor compression refrigeration cycles. Thermal Sci. Eng. Progress. 28, 101048 (2022)

    Article  CAS  Google Scholar 

  43. J.B. Bowles, C. Enrique Peldez, Fuzzy logic prioritization of failures in a system failure mode. Effects Crit. Anal. 50, 203–213 (1995)

    Google Scholar 

  44. M.J. Kalathil, V.R. Renjith, N.R. Augustine, Failure mode effect and criticality analysis using dempster shafer theory and its comparison with fuzzy failure mode effect and criticality analysis: a case study applied to LNG storage facility. Process. Saf. Environ. Prot.Saf. Environ. Prot. 138, 337–348 (2020)

    Article  CAS  Google Scholar 

  45. A.A.A.A. Al-Rashed, Effect of evaporator temperature on vapor compression refrigeration system. Alex. Eng. J. 50, 283–290 (2011)

    Article  CAS  Google Scholar 

  46. S. Khatoon, M.N. Karimi, Thermodynamic analysis of two evaporator vapor compression refrigeration system with low GWP refrigerants in automobiles. Int. J. Air-Cond. Refr. 31, 2 (2023)

    Article  Google Scholar 

  47. A.M. Kumar, S. Rajakarunakaran, P. Pitchipoo, R. Vimalesan, Fuzzy based risk prioritisation in an auto LPG dispensing station. Saf. Sci.. Sci. 101, 231–247 (2018)

    Article  Google Scholar 

  48. A. Mascia, A.M. Cirafici, A. Bongiovanni, G. Colotti, G. Lacerra, M. Di Carlo, F.A. Digilio, G.L. Liguori, A. Lanati, A. Kisslinger, A failure mode and effect analysis (FMEA)-based approach for risk assessment of scientific processes in non-regulated research laboratories. Accred. Qual. Assur.. Qual. Assur. 25, 311–321 (2020)

    Article  Google Scholar 

  49. V.R. Renjith, P.H. Kumar, D. Madhavan, Fuzzy FMECA (failure mode effect and criticality analysis) of LNG storage facility. J. Loss Prev. Process Ind. 56, 537–547 (2018)

    Article  CAS  Google Scholar 

  50. J. Ivančan, D. Lisjak, New FMEA risks ranking approach utilizing four fuzzy logic systems. Machines. 9, 292 (2021)

    Article  Google Scholar 

  51. Y. Yoon, H. Jeong, K.S. Lee, Adaptive defrost methods for improving defrosting efficiency of household refrigerator. Energy Convers. Manag. 157, 511–516 (2018)

    Article  Google Scholar 

  52. S. K. Akula, H. Salehfar, S. Behzadirafi, in 2022 North American Power Symposium (NAPS) (2022), pp. 1–6.

  53. Y.E. Priharanto, R.I. Yaqin, G. Marjianto, J.P. Siahaan, M.Z.L. Abrori, Risk assessment of the fishing vessel main engine by fuzzy-FMEA approach. J. Fail. Anal. Prev. 23, 822–836 (2023)

    Article  Google Scholar 

  54. L. Cruz-Rivero, M.L. Méndez-Hernández, C.E. Mar-Orozco, A.A. Aguilar-Lasserre, A. Barbosa-Moreno, J. Sánchez-Escobar, Functional evaluation using fuzzy FMEA for a non-invasive measurer for methane and carbone dioxide. Symmetry. 14, 421 (2022)

    Article  CAS  Google Scholar 

  55. K. Tanabe, Pareto’s 80/20 rule and the Gaussian distribution. Physica A A. 510, 635–640 (2018)

    Article  Google Scholar 

  56. A. Tayal, N.S. Kalsi, M.K. Gupta, D.Y. Pimenov, M. Sarikaya, C.I. Pruncu, Effectiveness improvement in manufacturing industry; trilogy study and open innovation dynamics. J. Open Innov. Technol. Market, Complex. 7, 1–21 (2021)

    Article  Google Scholar 

Download references

Acknowledgment

All authors thank all fishing vessel crews in Batam who have given their time and energy in collecting the necessary data. The author also thanks the Politeknik Kelautan dan Perikanan Dumai for supporting and facilitating the creation of fuzzy logic.

Funding

It is certified that the author has not received funding from any institution to carry out this research work.

Author information

Authors and Affiliations

  1. Department of Ship Machinery, Politeknik Kelautan dan Perikanan Dumai, Dumai, Riau, Indonesia

    Juniawan Preston Siahaan, Rizqi Ilmal Yaqin, Yuniar Endri Priharanto & M. Zaki Latif Abrori

  2. Department of Marine Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, East Java, Indonesia

    Nurhadi Siswantoro

Authors
  1. Juniawan Preston Siahaan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rizqi Ilmal Yaqin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuniar Endri Priharanto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. Zaki Latif Abrori
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nurhadi Siswantoro
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors have equal participation and teamwork to complete this research paper. All authors read and approved the manuscript made to the end.

Corresponding author

Correspondence to Juniawan Preston Siahaan.

Ethics declarations

Conflict of interest

The author declares that there is no potential conflict of interest regarding this article.

Ethical Approval

The author has been approved for ethical clearance with number 0030/KEPK/Adm2/II/2023 in connection with this research work.

Consent to Participate

Not applicable.

Consent to Publication

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Siahaan, J.P., Yaqin, R.I., Priharanto, Y.E. et al. Risk-Based Maintenance Strategies on Fishing Vessel Refrigeration Systems Using Fuzzy-FMEA. J Fail. Anal. and Preven. 24, 855–876 (2024). https://doi.org/10.1007/s11668-024-01878-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11668-024-01878-x

Keywords

Search

Navigation