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The Hidden Threat of Marine Pollution: A Risk Assessment of a Clogged Ship Sea Chest

Year 2024, EARLY VIEW, 1 - 1
https://doi.org/10.2339/politeknik.1297917

Abstract

In recent years, the effects of natural environmental degradation have been significantly felt on the world's oceans. Studies show that both human-made pollutants like plastics and marine organisms such as invasive species are now densely present in our seas. On the other hand, the cooling water systems, a critical component of ships, rely on seawater absorbed through the ship's sea chests. However, clogging sea chests due to marine pollution can render the ship's main and auxiliary engines inoperable, depriving the ship of its maneuverability. A ship that loses its main engine power and therefore its maneuverability is at risk of facing accidents such as collisions, groundings, fires, and explosions. This study conducted a risk analysis on the blockage of sea chests, a hidden threat of marine pollution. Using both Classical and Fuzzy Failure Mode and Effects Analysis (FMEA) methodologies, risks were quantitatively calculated through Risk Priority Numbers (RPN) and Fuzzy RPN (FRPN) scores. According to the Traditional FMEA findings, the top three highest-risk failure modes are HT006 - Main Engine High Lubricating Oil Temperature (143.520), HT007 - Main Engine High Jacket Water Temperature (111.720), and HT014 - Fire Pump Low Outlet Pressure and Flow Rate (100.590). The Fuzzy FMEA results indicated the top three highest-risk failure modes as HT006 - Main Engine High Lubricating Oil Temperature (5.58), HT014 - Fire Pump Low Outlet Pressure and Flow Rate (5.51), and HT013 - Insufficient Boiler Steam Condensate Efficiency (5.47). The obtained findings quantitatively demonstrate the impact of marine pollution on ship systems. Analysis results provides critical information for key maritime stakeholders such as seafarers, maritime companies, regulatory authorities, and the shipbuilding industry to prevent major maritime accidents caused by sea chest blockages in the future.

References

  • [1] Ceylan, B. O., Karatuğ, Ç., Akyuz, E., Arslanoğlu, Y., & Boustras, G., “A system theory (STAMP) based quantitative accident analysis model for complex engineering systems”, Safety science, 166: 106232, (2023).
  • [2] Theotokatos, G., Sfakianakis, K., & Vassalos, D., “Investigation of ship cooling system operation for improving energy efficiency”, Journal of Marine Science and Technology, 22: 38-50, (2017).
  • [3] Koroglu, T., & Sogut, O. S., “Developing criteria for advanced exergoeconomic performance analysis of thermal energy systems: Application to a marine steam power plant”, Energy, 267: 126582, (2023).
  • [4] Chaal, M., Bahootoroody, A., Basnet, S., Banda, O. A. V., & Goerlandt, F., “Towards system-theoretic risk assessment for future ships: A framework for selecting Risk Control Options”, Ocean Engineering, 259: 111797, (2022).
  • [5] Piola, R., Grandison, C., Shimeta, J., del Frate, A., & Leary, M., “Can vessel sea chest design improve fouling control coating performance?”, Ocean Engineering, 256: 111426, (2022).
  • [6] Coutts, A. D., & Taylor, M. D., “A preliminary investigation of biosecurity risks associated with biofouling on merchant vessels in New Zealand”, New Zealand Journal of Marine and Freshwater Research, 38(2): 215-229, (2004).
  • [7] Moser, C. S., Wier, T. P., First, M. R., Grant, J. F., Riley, S. C., Robbins-Wamsley, S. H., ... & Drake, L. A., “Quantifying the extent of niche areas in the global fleet of commercial ships: the potential for “super-hot spots” of biofouling”, Biological Invasions, 19(6): 1745-1759, (2017).
  • [8] Piola, R., & Grandison, C., “Assessments of quaternary ammonium compounds (QAC) for in-water treatment of mussel fouling in vessel internals and sea chests using an experimental seawater pipework system”, Biofouling, 33(1): 59-74, (2017).
  • [9] https://www.ipcc.ch/about/, “IPCC, 2024. The intergovermental panel on climate change”, (2024).
  • [10] Frey, M. A., Simard, N., Robichaud, D. D., Martin, J. L., & Therriault, T. W., “Fouling around: vessel sea-chests as a vector for the introduction and spread of aquatic invasive species”, Management of Biological Invasions, 5(1): 21, (2014).
  • [11] Ashton, G. V., Willis, K. J., Cook, E. J., & Burrows, M., “Distribution of the introduced amphipod, Caprella mutica Schurin, 1935 (Amphipoda: Caprellida: Caprellidae) on the west coast of Scotland and a review of its global distribution”, Hydrobiologia, 590(1): 31-41, (2007).
  • [12] McDonald, J. I., “Detection of the tropical mussel species Perna viridis in temperate Western Australia: possible association between spawning and a marine heat pulse”, Aquatic Invasions, 7(4), (2012).
  • [13] Pinsky, M. L., Selden, R. L., & Kitchel, Z. J., “Climate-driven shifts in marine species ranges: Scaling from organisms to communities”, Annual review of marine science, 12: 153-179, (2020).
  • [14] Davidson, I., Cahill, P., Hinz, A., Major, R., Kluza, D., Scianni, C., & Georgiades, E., “Biofouling occlusion of ships’ internal seawater systems: operational, economic, and biosecurity consequences”, Biofouling, 39(4): 410-426, (2023).
  • [15] Uflaz, E., Akyüz, E., Bolat, F., Bolat, P., & Arslan, Ö., “Investigation of the effects of mucilage on maritime operation”, Journal of the Black Sea/Mediterranean Environment, 27(2): 140-153, (2021).
  • [16] Usluer, H. B., “Effects of Mucilage on Safety Navigation in the Turkish Straits”, International Journal of Environment and Geoinformatics, 9(3): 84-90, (2022).
  • [17] Arndt, E., Robinson, A., Hester, S., Woodham, B., Wilkinson, P., & Gorgula, S., “Factors that influence vessel biofouling and its prevention and management”, Final report for CEBRA Project, 190803, (2021).
  • [18] Ceylan, B. O., “Marine diesel engine turbocharger fouling phenomenon risk assessment application by using fuzzy FMEA method”, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 14750902231208848, (2023).
  • [19] Goerlandt, F., & Montewka, J., “Maritime transportation risk analysis: Review and analysis in light of some foundational issues”, Reliability Engineering & System Safety, 138: 115-134, (2015).
  • [20] Yorulmaz, M., & Sezen, K., “Denizcilik Alanında Kullanılan Risk Analizi Yöntemleri ve Fine Kinney Yöntemiyle Bir Uygulama”, Afet ve Risk Dergisi, 6(3): 622-637, (2023).
  • [21] Sakar, C., & Sokukcu, M., “Dynamic analysis of pilot transfer accidents”, Ocean Engineering, 287: 115823, (2023).
  • [22] Tunçel, A. L., Akyuz, E., & Arslan, O., “An Extended Event Tree Risk Analysis Under Fuzzy Logic Environment: The Case of Fire in Ship Engine Room”, Journal of ETA Maritime Science, 9(3), (2021).
  • [23] Basnet, S., “Managing risks in maritime remote pilotage using the basis of the Formal Safety Assessment”, (2023).
  • [24] Tonoğlu, F., Atalar, F., Başkan, İ. B., Yildiz, S., Uğurlu, Ö., & Wang, J., “A new hybrid approach for determining sector-specific risk factors in Turkish Straits: Fuzzy AHP-PRAT technique”, Ocean Engineering, 253: 111280, (2022).
  • [25] Aydin, M., Arici, S. S., Akyuz, E., & Arslan, O., “A probabilistic risk assessment for asphyxiation during gas inerting process in chemical tanker ship”, Process Safety and Environmental Protection, 155: 532-542, (2021).
  • [26] Başhan, V., & Demirel, H., “Application of fuzzy dematel technique to assess most common critical operational faults of marine boilers”, Politeknik Dergisi, 22(3): 545-555, (2019).
  • [27] Yorulmaz, M., & YEĞİN, A. O., “Liman işletmelerinde tehlikeli madde elleçlenmesine ilişkin Fine-Kinney ve FMEA yöntemleri ile risk analizi”, R&S-Research Studies Anatolia Journal, 6(1): 1-37, (2023).
  • [28] Ceylan, B. O., “Shipboard compressor system risk analysis by using rule-based fuzzy FMEA for preventing major marine accidents” Ocean Engineering, 272: 113888, (2023).
  • [29] Priharanto, Y. E., Yaqin, R. I., Marjianto, G., Siahaan, J. P., & Abrori, M. Z. L., “Risk assessment of the fishing vessel main engine by fuzzy-fmea approach”, Journal of Failure Analysis and Prevention, 23(2): 822-836, (2023).
  • [30] Yılmaz, F., & İlhan, M. N., “Türk Bayraklı gemilerin karıştığı deniz kazaları ve denizcilere etkilerine ilişkin bir analiz”, Gemi ve Deniz Teknolojisi, (211): 80-95, (2018).
  • [31] Çakır, E., & Kamal, B., “İstanbul Boğazı’ndaki ticari gemi kazalarının karar ağacı yöntemiyle analizi”, Aquatic Research, 4(1): 10-20, (2020).
  • [32] Liu, H. C., Liu, L., & Liu, N., “Risk evaluation approaches in failure mode and effects analysis: A literature review”, Expert systems with applications, 40(2): 828-838, (2013).
  • [33] Karatuğ, Ç., Ceylan, B. O., & Arslanoğlu, Y., “A risk assessment of scrubber use for marine transport by rule-based fuzzy FMEA”, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 238(1): 114-125, (2024).
  • [34] Chanamool, N., & Naenna, T., “Fuzzy FMEA application to improve decision-making process in an emergency department”, Applied Soft Computing, 43: 441-453, (2016).
  • [35] Goksu, S., & Arslan, O., “A quantitative dynamic risk assessment for ship operation using the fuzzy FMEA: The case of ship berthing/unberthing operation”, Ocean Engineering, 287: 115548, (2023).
  • [36] Zadeh, L., “Fuzzy sets”, Inform Control, 8: 338-353, (1965).
  • [37] Aktas, İ. S., Memlik, T., & Sözen, A., “Akıllı bir şebekedeki risk indikatörlerinin bulanık analitik hiyerarşi prosesi ile modellenmesi”, 1-1, Politeknik Dergisi, (2020).
  • [38] Karamollaoğlu, H., Yücedağ, İ., & Dogru, İ., “Risk assessment for electricity generation management process with swara based fuzzy TOPSIS method”, Politeknik Dergisi, 1-1, (2021).
  • [39] Ahmed, S., & Gu, X. C., “Accident-based FMECA study of Marine boiler for risk prioritization using fuzzy expert system”, Results in Engineering, 6: 100123, (2020).
  • [40] Akyuz, E., Akgun, I., & Celik, M., “A fuzzy failure mode and effects approach to analyse concentrated inspection campaigns on board ships”, Maritime Policy & Management, 43(7): 887-908, (2016).
  • [41] Pillay, A., & Wang, J., “Modified failure mode and effects analysis using approximate reasoning”, Reliability Engineering & System Safety, 79(1): 69-85, (2003).
  • [42] Ceylan, B. O., Karatuğ, Ç., Ejder, E., Uyanık, T., & Arslanoğlu, Y., “Risk assessment of sea chest fouling on the ship machinery systems by using both FMEA method and ERS process”, Australian Journal of Maritime & Ocean Affairs, 15(4): 414-433, (2023).
  • [43] Balaraju, J., Raj, M. G., & Murthy, C. S., “Fuzzy-FMEA risk evaluation approach for LHD machine–A case study”, Journal of Sustainable Mining, 18(4): 257-268, (2019).
  • [44] Dağsuyu, C., Göçmen, E., Narlı, M., & Kokangül, A., “Classical and fuzzy FMEA risk analysis in a sterilization unit”, Computers & Industrial Engineering, 101: 286-294, (2016).
  • [45] Kaptan, M., Sivri, N., Blettler, M. C., & Uğurlu, Ö., “Potential threat of plastic waste during the navigation of ships through the Turkish straits”, Environmental Monitoring and Assessment, 192(8): 508, (2020).

Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi

Year 2024, EARLY VIEW, 1 - 1
https://doi.org/10.2339/politeknik.1297917

Abstract

Doğal çevre tahribatının etkileri, son yıllarda dünya denizleri üzerinde ciddi şekilde hissedilmektedir. Çalışmalar, gerek plastik gibi insan kaynaklı kirleticilerin gerekse istilacı türler gibi deniz canlılarının artık denizlerimizde yoğun olarak bulunduğunu göstermektedir. Diğer bir yandan gemilerin kritik bir unsuru olan soğutma suyu sistemleri, gemi kinistin sandıklarından emilen deniz suyu ile hayat bulmaktadır. Ancak, deniz kirliliği kaynaklı kinistin tıkanıklığı, geminin ana ve yardımcı makinelerini çalışamaz duruma getirerek, gemiyi manevra kabiliyetinden mahrum bırakmaktadır. Ana makine gücünü ve dolayısıyla manevra yeteneğini kaybeden gemi ise çarpma, çatışma, karaya oturma, yangın ve patlama gibi felaketlerle yüzleşme riski taşımaktadır. Bu çalışma, deniz kirliliğinin görünmeyen tehlikesi olan kinistin sandığı tıkanıklığı üzerine bir risk analizi yürütmüştür. Çalışmada hem Klasik hem de Bulanık Hata Türü ve Etkileri Analizi (HTEA) yöntemleri kullanılarak, hata türlerine ilişkin riskler Risk Öncelik Sayısı (RÖS) ve Bulanık RÖS (BRÖS) puanlarıyla sayısal olarak hesaplanmıştır. Klasik HTEA bulgularına göre, en riskli 3 hata türü, HT006 - Ana Makine Yüksek Yağlama Yağı Sıcaklığı (143.520), HT007 - Ana Makine Yüksek Ceket Suyu Sıcaklığı (111.720), HT014 - Yangın Pompası Düşük Çıkış Basıncı ve Debisi (100.590) olarak tespit edilmiştir. Bulanık HTEA sonuçlarında ise en riskli 3 hata türü HT006 - Ana Makine Yüksek Yağlama Yağı Sıcaklığı (5.58), HT014 - Yangın Pompası Düşük Çıkış Basıncı ve Debisi (5.51) ve HT013 – Kazan Yetersiz Buhar Yoğuşma Verimliliği (5.47) olarak ortaya konmuştur. Elde edilen bulgular, deniz kirliliğinin gemi sistemleri üzerindeki etkilerini sayısal olarak ortaya koymaktadır. Bu veriler, gemi adamları, denizcilik şirketleri, denetleme otoriteleri ve gemi inşa sektörü gibi temel denizcilik paydaşlarına, gelecekte oluşabilecek kinistin sandığı tıkanıklığı kaynaklı büyük deniz kazalarını önlemek adına önemli bilgiler sunmaktadır.

References

  • [1] Ceylan, B. O., Karatuğ, Ç., Akyuz, E., Arslanoğlu, Y., & Boustras, G., “A system theory (STAMP) based quantitative accident analysis model for complex engineering systems”, Safety science, 166: 106232, (2023).
  • [2] Theotokatos, G., Sfakianakis, K., & Vassalos, D., “Investigation of ship cooling system operation for improving energy efficiency”, Journal of Marine Science and Technology, 22: 38-50, (2017).
  • [3] Koroglu, T., & Sogut, O. S., “Developing criteria for advanced exergoeconomic performance analysis of thermal energy systems: Application to a marine steam power plant”, Energy, 267: 126582, (2023).
  • [4] Chaal, M., Bahootoroody, A., Basnet, S., Banda, O. A. V., & Goerlandt, F., “Towards system-theoretic risk assessment for future ships: A framework for selecting Risk Control Options”, Ocean Engineering, 259: 111797, (2022).
  • [5] Piola, R., Grandison, C., Shimeta, J., del Frate, A., & Leary, M., “Can vessel sea chest design improve fouling control coating performance?”, Ocean Engineering, 256: 111426, (2022).
  • [6] Coutts, A. D., & Taylor, M. D., “A preliminary investigation of biosecurity risks associated with biofouling on merchant vessels in New Zealand”, New Zealand Journal of Marine and Freshwater Research, 38(2): 215-229, (2004).
  • [7] Moser, C. S., Wier, T. P., First, M. R., Grant, J. F., Riley, S. C., Robbins-Wamsley, S. H., ... & Drake, L. A., “Quantifying the extent of niche areas in the global fleet of commercial ships: the potential for “super-hot spots” of biofouling”, Biological Invasions, 19(6): 1745-1759, (2017).
  • [8] Piola, R., & Grandison, C., “Assessments of quaternary ammonium compounds (QAC) for in-water treatment of mussel fouling in vessel internals and sea chests using an experimental seawater pipework system”, Biofouling, 33(1): 59-74, (2017).
  • [9] https://www.ipcc.ch/about/, “IPCC, 2024. The intergovermental panel on climate change”, (2024).
  • [10] Frey, M. A., Simard, N., Robichaud, D. D., Martin, J. L., & Therriault, T. W., “Fouling around: vessel sea-chests as a vector for the introduction and spread of aquatic invasive species”, Management of Biological Invasions, 5(1): 21, (2014).
  • [11] Ashton, G. V., Willis, K. J., Cook, E. J., & Burrows, M., “Distribution of the introduced amphipod, Caprella mutica Schurin, 1935 (Amphipoda: Caprellida: Caprellidae) on the west coast of Scotland and a review of its global distribution”, Hydrobiologia, 590(1): 31-41, (2007).
  • [12] McDonald, J. I., “Detection of the tropical mussel species Perna viridis in temperate Western Australia: possible association between spawning and a marine heat pulse”, Aquatic Invasions, 7(4), (2012).
  • [13] Pinsky, M. L., Selden, R. L., & Kitchel, Z. J., “Climate-driven shifts in marine species ranges: Scaling from organisms to communities”, Annual review of marine science, 12: 153-179, (2020).
  • [14] Davidson, I., Cahill, P., Hinz, A., Major, R., Kluza, D., Scianni, C., & Georgiades, E., “Biofouling occlusion of ships’ internal seawater systems: operational, economic, and biosecurity consequences”, Biofouling, 39(4): 410-426, (2023).
  • [15] Uflaz, E., Akyüz, E., Bolat, F., Bolat, P., & Arslan, Ö., “Investigation of the effects of mucilage on maritime operation”, Journal of the Black Sea/Mediterranean Environment, 27(2): 140-153, (2021).
  • [16] Usluer, H. B., “Effects of Mucilage on Safety Navigation in the Turkish Straits”, International Journal of Environment and Geoinformatics, 9(3): 84-90, (2022).
  • [17] Arndt, E., Robinson, A., Hester, S., Woodham, B., Wilkinson, P., & Gorgula, S., “Factors that influence vessel biofouling and its prevention and management”, Final report for CEBRA Project, 190803, (2021).
  • [18] Ceylan, B. O., “Marine diesel engine turbocharger fouling phenomenon risk assessment application by using fuzzy FMEA method”, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 14750902231208848, (2023).
  • [19] Goerlandt, F., & Montewka, J., “Maritime transportation risk analysis: Review and analysis in light of some foundational issues”, Reliability Engineering & System Safety, 138: 115-134, (2015).
  • [20] Yorulmaz, M., & Sezen, K., “Denizcilik Alanında Kullanılan Risk Analizi Yöntemleri ve Fine Kinney Yöntemiyle Bir Uygulama”, Afet ve Risk Dergisi, 6(3): 622-637, (2023).
  • [21] Sakar, C., & Sokukcu, M., “Dynamic analysis of pilot transfer accidents”, Ocean Engineering, 287: 115823, (2023).
  • [22] Tunçel, A. L., Akyuz, E., & Arslan, O., “An Extended Event Tree Risk Analysis Under Fuzzy Logic Environment: The Case of Fire in Ship Engine Room”, Journal of ETA Maritime Science, 9(3), (2021).
  • [23] Basnet, S., “Managing risks in maritime remote pilotage using the basis of the Formal Safety Assessment”, (2023).
  • [24] Tonoğlu, F., Atalar, F., Başkan, İ. B., Yildiz, S., Uğurlu, Ö., & Wang, J., “A new hybrid approach for determining sector-specific risk factors in Turkish Straits: Fuzzy AHP-PRAT technique”, Ocean Engineering, 253: 111280, (2022).
  • [25] Aydin, M., Arici, S. S., Akyuz, E., & Arslan, O., “A probabilistic risk assessment for asphyxiation during gas inerting process in chemical tanker ship”, Process Safety and Environmental Protection, 155: 532-542, (2021).
  • [26] Başhan, V., & Demirel, H., “Application of fuzzy dematel technique to assess most common critical operational faults of marine boilers”, Politeknik Dergisi, 22(3): 545-555, (2019).
  • [27] Yorulmaz, M., & YEĞİN, A. O., “Liman işletmelerinde tehlikeli madde elleçlenmesine ilişkin Fine-Kinney ve FMEA yöntemleri ile risk analizi”, R&S-Research Studies Anatolia Journal, 6(1): 1-37, (2023).
  • [28] Ceylan, B. O., “Shipboard compressor system risk analysis by using rule-based fuzzy FMEA for preventing major marine accidents” Ocean Engineering, 272: 113888, (2023).
  • [29] Priharanto, Y. E., Yaqin, R. I., Marjianto, G., Siahaan, J. P., & Abrori, M. Z. L., “Risk assessment of the fishing vessel main engine by fuzzy-fmea approach”, Journal of Failure Analysis and Prevention, 23(2): 822-836, (2023).
  • [30] Yılmaz, F., & İlhan, M. N., “Türk Bayraklı gemilerin karıştığı deniz kazaları ve denizcilere etkilerine ilişkin bir analiz”, Gemi ve Deniz Teknolojisi, (211): 80-95, (2018).
  • [31] Çakır, E., & Kamal, B., “İstanbul Boğazı’ndaki ticari gemi kazalarının karar ağacı yöntemiyle analizi”, Aquatic Research, 4(1): 10-20, (2020).
  • [32] Liu, H. C., Liu, L., & Liu, N., “Risk evaluation approaches in failure mode and effects analysis: A literature review”, Expert systems with applications, 40(2): 828-838, (2013).
  • [33] Karatuğ, Ç., Ceylan, B. O., & Arslanoğlu, Y., “A risk assessment of scrubber use for marine transport by rule-based fuzzy FMEA”, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 238(1): 114-125, (2024).
  • [34] Chanamool, N., & Naenna, T., “Fuzzy FMEA application to improve decision-making process in an emergency department”, Applied Soft Computing, 43: 441-453, (2016).
  • [35] Goksu, S., & Arslan, O., “A quantitative dynamic risk assessment for ship operation using the fuzzy FMEA: The case of ship berthing/unberthing operation”, Ocean Engineering, 287: 115548, (2023).
  • [36] Zadeh, L., “Fuzzy sets”, Inform Control, 8: 338-353, (1965).
  • [37] Aktas, İ. S., Memlik, T., & Sözen, A., “Akıllı bir şebekedeki risk indikatörlerinin bulanık analitik hiyerarşi prosesi ile modellenmesi”, 1-1, Politeknik Dergisi, (2020).
  • [38] Karamollaoğlu, H., Yücedağ, İ., & Dogru, İ., “Risk assessment for electricity generation management process with swara based fuzzy TOPSIS method”, Politeknik Dergisi, 1-1, (2021).
  • [39] Ahmed, S., & Gu, X. C., “Accident-based FMECA study of Marine boiler for risk prioritization using fuzzy expert system”, Results in Engineering, 6: 100123, (2020).
  • [40] Akyuz, E., Akgun, I., & Celik, M., “A fuzzy failure mode and effects approach to analyse concentrated inspection campaigns on board ships”, Maritime Policy & Management, 43(7): 887-908, (2016).
  • [41] Pillay, A., & Wang, J., “Modified failure mode and effects analysis using approximate reasoning”, Reliability Engineering & System Safety, 79(1): 69-85, (2003).
  • [42] Ceylan, B. O., Karatuğ, Ç., Ejder, E., Uyanık, T., & Arslanoğlu, Y., “Risk assessment of sea chest fouling on the ship machinery systems by using both FMEA method and ERS process”, Australian Journal of Maritime & Ocean Affairs, 15(4): 414-433, (2023).
  • [43] Balaraju, J., Raj, M. G., & Murthy, C. S., “Fuzzy-FMEA risk evaluation approach for LHD machine–A case study”, Journal of Sustainable Mining, 18(4): 257-268, (2019).
  • [44] Dağsuyu, C., Göçmen, E., Narlı, M., & Kokangül, A., “Classical and fuzzy FMEA risk analysis in a sterilization unit”, Computers & Industrial Engineering, 101: 286-294, (2016).
  • [45] Kaptan, M., Sivri, N., Blettler, M. C., & Uğurlu, Ö., “Potential threat of plastic waste during the navigation of ships through the Turkish straits”, Environmental Monitoring and Assessment, 192(8): 508, (2020).
There are 45 citations in total.

Details

Primary Language Turkish
Subjects Engineering, Marine Vehicles Management Engineering
Journal Section Research Article
Authors

Bulut Ozan Ceylan 0000-0003-1182-3566

Early Pub Date August 1, 2024
Publication Date
Submission Date May 16, 2023
Published in Issue Year 2024 EARLY VIEW

Cite

APA Ceylan, B. O. (2024). Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi. Politeknik Dergisi1-1. https://doi.org/10.2339/politeknik.1297917
AMA Ceylan BO. Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi. Politeknik Dergisi. Published online August 1, 2024:1-1. doi:10.2339/politeknik.1297917
Chicago Ceylan, Bulut Ozan. “Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi”. Politeknik Dergisi, August (August 2024), 1-1. https://doi.org/10.2339/politeknik.1297917.
EndNote Ceylan BO (August 1, 2024) Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi. Politeknik Dergisi 1–1.
IEEE B. O. Ceylan, “Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi”, Politeknik Dergisi, pp. 1–1, August 2024, doi: 10.2339/politeknik.1297917.
ISNAD Ceylan, Bulut Ozan. “Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi”. Politeknik Dergisi. August 2024. 1-1. https://doi.org/10.2339/politeknik.1297917.
JAMA Ceylan BO. Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi. Politeknik Dergisi. 2024;:1–1.
MLA Ceylan, Bulut Ozan. “Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi”. Politeknik Dergisi, 2024, pp. 1-1, doi:10.2339/politeknik.1297917.
Vancouver Ceylan BO. Deniz Kirliliğinin Görünmeyen Tehlikesi: Gemi Kinistin Sandığı Tıkanıklığı Üzerine Bir Risk Analizi. Politeknik Dergisi. 2024:1-.