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DOI :10.26650/JTL.2022.1020313   IUP :10.26650/JTL.2022.1020313    Tam Metin (PDF)

Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi

Volkan GençAşkın ÖzdağoğluMurat Kemal Keleş

Otomobillerde kullanılan motor yağlarının; yakıt sarfiyatı, motorun parçalarında oluşan sürtünmelerin etkisiyle meydana gelecek aşınma, motorun verimliliği ve performansı gibi bir çok unsura etkisi bulunmaktadır. Bu yüzden kaliteli bir motor yağı seçilmesi otomobilin motorunun performansını artırmak, verimli kullanmak ve ömrünü uzatmak açısından önemlidir. Bu çalışmanın amacı, hususi otomobillere yönelik otomotiv sektöründe öncü markaların Türkiye’de satışa sunmuş olduğu 5w30 motor yağl alternatifleri arasından en optimal olanı belirlemektir. Bu amaca yönelik olarak konusunda uzman olan teknik kişiler tarafından sekiz adet kriter belirlenmiştir. Kriterlerin ağırlıkları ılık iklime sahip İzmir ve karasal iklime sahip Erzurum düşünülerek iki farklı iklim şartına göre yeni ağırlıklandırma yöntemlerinden olan BWM ve FUCOM yöntemleri ile bulunmuştur. Çalışma kapsamındaki beş motor yağı alternatifi ise İzmir ve Erzurum için bulunan kriter ağırlıklarına göre MABAC ve MAIRCA yöntemleri ile sıralanmıştır. Analiz sonuçlarına göre kriter ağırlıklandırmasında; İzmir için ilk sırada “viskozite 100” kriteri çıkarken Erzurum için ise “soğuk marş simulatörü” kriteri birinci olmuştur. Gerek İzmir gerekse de Erzurum için son sırada yer alan kriter ise “Viskozite indeksi” kriteridir. İzmir ve Erzurum iklim şartlarına göre MAIRCA ve MABAC yöntemleri ile yapılan motor yağlarının değerlendirilmesinde ise İzmir ve Erzurum için motor yağı alterantiflerinin sıralaması aynı çıkmıştır. Analizler sonunda bulunan sonuçlar karşılaştırılmış ve önerilerde bulunulmuştur.

DOI :10.26650/JTL.2022.1020313   IUP :10.26650/JTL.2022.1020313    Tam Metin (PDF)

Evaluation of Automobile Engine Oil Alternatives with FUCOM, MAIRCA, MABAC and BWM Methods

Volkan GençAşkın ÖzdağoğluMurat Kemal Keleş

Engine oils used in automobiles have an impact on many factors such as fuel consumption, wear that will occur with the effect of friction in the parts of the engine, efficiency and performance of the engine. Therefore, choosing a quality engine oil is important in terms of increasing the performance of the car’s engine, using it efficiently and prolonging its life. The aim of this study is to determine the most optimal one among the 5w30 engine oil alternatives for private cars offered by leading brands in the automotive industry in Turkey. For this purpose, eight criteria have been determined by technical people who are experts in their fields. The weights of the criteria were found by considering two different climatic conditions, namely İzmir with a warm climate and Erzurum with a continental climate, using the new weighting methods BWM and FUCOM. The five engine oil alternatives were listed according to the criteria weights found for İzmir and Erzurum by MABAC and MAIRCA methods. In the light of the analysis, the “viscosity 100” criterion was the first for İzmir, the “cold starting simulator” criterion was the first for Erzurum. The last criterion for both İzmir and Erzurum is the “Viscosity index” criterion. In the evaluation of engine oils made by MAIRCA and MABAC methods according to the climate conditions of Izmir and Erzurum, the order of engine oil alternatives for Izmir and Erzurum was the same. In the last pahse the results were compared and suggestions were made.


GENİŞLETİLMİŞ ÖZET


Engine oil is a liquid that forms a protective film layer on the moving parts of the engine, reducing wear and friction, as well as preventing rust and corrosion with the compounds it contains. This fluid also assists the vehicle cooling system at the temperature point by lowering heat created during engine operation, cooling it in the crankcase, and re-joining it in the system cycle with each oil circulation. Many elements, such as engine performance, wear due to friction in engine parts, and fuel consumption, are directly influenced by the engine oil used in an automobile. As a result, selecting a high-quality engine oil is critical if you want to keep your car’s engine running longer and more efficiently.

The goal of this research is to find the best 5w30 engine oil for private cars among the 5w30 engine oils available for sale in Turkey by the industry’s main companies. The WSS-M2C913-D specification has been determined for the five mineral engine oil replacements under consideration. Experts established the eight criteria employed in the study. “Viscosity index,” “Viscosity 40-100 °C mm2/S,” “Density,” “Flash Point,” “Flow Point,” “Cold Start,” and “Ash Sulphate value” are the variables to examine while picking the best engine oil. A choice will be made between five distinct mineral oil brand options based on these parameters. The manufacturers’ ASTM (American Society for Testing and Materials) procedures yielded test results that provided values for the technical parameters that influence selection. Engine oil selection criteria were analyzed for two alternative scenarios, taking into account the conditions in Izmir province, which has a pleasant climate, and Erzurum province, which has a harsh continental environment.

The FUCOM, MAIRCA, MABAC, and BWM approaches, which are innovative methodologies, were applied in the study. The criteria weights were determined separately using the FUCOM and BWM multi-criteria decision-making procedures, based on the climate circumstances of two different regions, namely the Aegean and continental climates. MAIRCA and MABAC methodologies are used to rank the five mineral motor oil alternatives according to the criteria weights obtained in both climatic conditions. Owing to the fact that there are negative values in the matrix, the MAIRCA and MABAC approaches were preferred to be able to pick amongst options.

According to the findings of the analysis, the viscosity 100 criterion is first for Izmir, and the cold start simulator criterion is first for Erzurum, in a weighing of the criteria based on the conditions of Izmir and Erzurum. The Viscosity index criterion is the eighth and final criterion in the context of both zmir and Erzurum. The identical alternatives was found for both Izmir and Erzurum in the engine oil rankings established according to different climate conditions using the MAIRCA and MABAC methodologies. The main reason for this is that every option that complies with the WSS-M2C913-D standard in Turkey and is available on the market can perform its function in a variety of climatic and temperature conditions throughout our country’s geography. The study’s fundamental disadvantage is that it is limited to the geography of Turkey; if it had been conducted over a wider range of foreign geographies, the results could have varied according to climatic circumstances. 

There was no study discovered in the literature that used Multi-Criteria Decision Making (MCDM) methodologies to choose engine oil options for autos. This will be the first study in the literature to establish and weight engine oil selection criteria for automobiles based on different environmental circumstances, and then use MCDM methods to select the best engine oil alternative. As a result, it is expected to be innovative and contribute to the literature. Furthermore, it is anticipated that this research will be advantageous to both automobile consumers and employees in the automotive industry, as well as engine oil manufacturers and marketers. 


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Referanslar

  • Arsic, S. N., Pamucar, D., Suknovic, M. ve Janosevic, M. (2019). Menu Evaluation Based on Rough MAIRCA and BW Methods. Serbian Journal of Management, 14(1), 27-48. google scholar
  • Avcı, A. (2009). Bir Kargo Firmasına Ait 6 Adet Diesel Aracın Optimum Yağ Değişim Süreçlerinin Ekonomik Etüdü. (Yayımlanmamış yüksek lisans tezi). Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü, Makine Mühendisliği Anabilim Dalı, İstanbul. google scholar
  • Ayçin, E. (2020). Personel Seçim Sürecinde CRITIC ve MAIRCA Yöntemlerinin Kullanılması. İşletme, 1(1), 1-12. google scholar
  • Bakır, M. (2019). SWARA ve MABAC Yöntemleri ile Havayolu Işletmelerinde Ewom’a Dayalı Memnuniyet Düzeyinin Analizi, İzmir İktisat Dergisi, 34 (1), 51-66. Doi: 10.24988/ije.2019341787. google scholar
  • Biswas, T. K. ve Das, M. C. (2018). Selection of Commercially Available Electric Vehicle using Fuzzy AHP-MABAC. Journal of The Institution of Engineers (India): Series C, 100(3), 531-537, https://doi. org/10.1007/s40032-018-0481-3. google scholar
  • Bozanic, D., Tesic, D. ve Kocic, J. (2019). Multi-Criteria FUCOM-Fuzzy MABAC Model for The Selection of Location for Construction of Single-Span Bailey Bridge. Decision Making: Applications in Management and Engineering, 2(1), 132-146. DOI:_ https://doi.org/10.31181/dmame1901132b. google scholar
  • Bozanic, D., Tesic, D., ve Milic, A. (2020). Multicriteria Decision Making Model With Z-Numbers Based on FUCOM and MABAC Model. Decision Making: Applications in Management and Engineering, 3(2), 19-36. DOI: https://doi.org/10.31181/dmame2003019d. google scholar
  • Cao, Q., Esangbedo, M. O., Bai, S., & Esangbedo, C.O. (2019). Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation. Energies, 12(13), 2481. https://doi.org/10.3390/en12132481. google scholar
  • Castrol, (2020). Castrol MAGNATEC STOP-START 5W-30 A5. Erişim tarihi: 20.09.2020, https://msdspds. castrol.com/bpglis/FusionPDS.nsf/Files/8DF7EB67C6A8566980257F6C0059DA45/$File/BPXE-A7YAPZ.pdf. google scholar
  • Cirovic, G., Pamucar, D. ve Popovic-Miletic, N. (2020). Multi-Criteria Model Based on Linguistic Neutrosophic Numbers: The Selection of Unmanned Aircraft. Proceedings of International Conference on Contemporary Theory And Practice in Construction XIV, 277-287, I Doi 10.7251/STP2014277C. google scholar
  • Ecer, F. (2021). FUCOM Sübjektif Ağırlıklandırma Yöntemi Ile Rüzgâr Çiftliği Yer Seçimini Etkileyen Faktörlerin Analizi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 27(1), 24-34. google scholar
  • Genç, V. (Görüşme tarihi: 20.12.2021). Ağır Vasıta Sürüş Eğitmeni, MEB, Motorlu taşıt usta öğreticiliği sertifikası, Sertifika tarihi: 23.08.2019, Pub. L. No. 198661220190062700000. google scholar
  • Gigovic, L., Pamucar, D., Bajic, Z. ve Milicevic, M., (2016). The Combination of Expert Judgment and GIS-MAIRCA Analysis for the Selection of Sites for Ammunition Depots. Sustainability, 8(4), 372, 1-30, doi:10.3390/su8040372. google scholar
  • Gigovic, L., Pamucar, D., Bozanic, D. ve Ljubojevic, S. (2017). Application of The Gis-Danp-Mabac Multi-Criteria Model Forselecting The Location of Wind Farms: A Case Study of Vojvodina, Serbia. Renewable Energy. 103. 501-521. http://dx.doi.org/10.1016/j.renene.2016.11.057. google scholar
  • Gupta, Himanshu. (2018). Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS. Journal of Environmental Management, 226, 201-216. Doi: 10.1016/j. jenvman.2018.08.005. google scholar
  • Halis, S. (2016). Araç Kullanım Sürelerinin Motor Yağ Viskozitesine Etkisinin Deneysel Olarak İncelenmesi. (Yayımlanmamış yüksek lisans tezi). Pamukkale Üniversitesi Fen Bilimleri Enstitüsü Otomotiv Mühendisliği Anabilim Dalı, Denizli. google scholar
  • İpek, R. İ. ve Erdoğan, M. (2006). Motor Yağı Takviyelerinin, Aşınma Mekanizmalarina Etkisinin Deneysel Araştırılması. Dumlupınar Üniversitesi, Fen Bilimleri Enstitüsü Dergisi, 12, 67-78. google scholar
  • Ji, P., Zhang, H. Y., ve Wang, J. Q. (2018). Selecting an outsourcing provider based on the combined MABAC-ELECTRE method using single-valued neutrosophic linguistic sets. Computers & Industrial Engineering, 120, 429-441. https://doi.org/10.1016/j.cie.2018.05.012. google scholar
  • Kıran, M. B. (2019). Ülke İş Sağlığı ve Güvenliği Performanslarını Değerlendirmek Amacıyla MAIRCA Yönteminin Dört Farklı Ağırlıklandırma Yaklaşımı ile Uygulanması. (Yayımlanmamış yüksek lisans tezi). Başkent Üniversitesi Fen Bilimleri Enstitüsü, Ankara. google scholar
  • Mamak Ekinci, E.B. ve Can, G.F. (2018). Algılanan İş Yükü ve Çalışma Duruşları Dikkate Alınarak Operatörlerin Ergonomik Risk Düzeylerinin Çok Kriterli Karar Verme Yaklaşımı ile Değerlendirilmesi. Ergonomi, 1(2), 77-91. https://doi.org/10.33439/ergonomi.478732. google scholar
  • Matic, B., Jovanovic, S., Das, D. K., Zavadskas, E. K., Stevic, Z., Sremac, S. ve Marinkovic, M. (2019). A New Hybrid MCDM Model: Sustainable Supplier Selection in A Construction Company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353. google scholar
  • Mobil, (2020). Mobil Super 3000 X1 FORMULA FE 5W-30. Erişim tarihi: 20.09.2020, https://www.mobil. com/tr-tr/passenger-vehicle-lube/pds/gl-xx-mobil-super-3000-x1-formula-fe-5w30. google scholar
  • Motul, (2020). Motul 8100 ECO-NERGY 5W-30. Erişim tarihi: 20.09.2020, https://d23zpyj32c5wn3. cloudfront.net/images/product_descriptions/technical_data_sheets/42560/8100_ECO-NERGY_5W-30_ tr_TR_motul_20190827.pdf?1566916094. google scholar
  • Nabeeh, N.A., Abdel-Monem, A., ve Abdelmouty, A. (2020). A Novel Methodology for Assessment of Hospital Service according to BWM, MABAC, PROMETHEE II. Neutrosophic Sets and Systems, 31(1), 63-79. google scholar
  • Nunic, Z. (2018). Evaluation and Selection of The Pvc Carpentry Manufacturer Using The FUCOM-MABAC Model. Operational Research in Engineering Sciences: Theory and Applications. Theory Appl. 1(1), 13-28. DOI: https://doi.org/10.31181/oresta190101s. google scholar
  • Özçelik, A.E. (2004). Konya İlinde Otomotiv Taşıtlarında Motor Yağ-Yakıt Seçimi ve Bakım Alışkanlıklarının Belirlenmesi. (Yayımlanmamış yüksek lisans tezi). Selçuk Üniversitesi Fen Bilimleri Enstitüsü, Makine Eğitimi Anabilim Dalı, Konya. google scholar
  • Pamucar, D. S., Tarle, S. P., ve Parezanovic, T. (2018c). New Hybrid Multi-Criteria Decision-Making Dematel Mairca Model: Sustainable Selection of A Location for The Development of Multimodal Logistics Centre. Economic Research-Ekonomska Istrazivanja, 31 (1), 1641-1665. Doi:10.1080/1331677X.2018.1506706. google scholar
  • Pamucar, D. ve Cirovic, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42 (6), 3016-3028. https://doi.org/10.1016/j.eswa.2014.11.057. google scholar
  • Pamucar, D., Lukovac, V., Bozanic, D. ve Komazec, N. (2018b). Multi-criteria FUCOM-MAIRCA Model for The Evaluation of Level Crossings: Case Study in The Republic of Serbia. Operational Research in Engineering Sciences: Theory and Applications, 1(1), 108-129. DOI: https://doi.org/10.31181/ oresta190101s. google scholar
  • Pamucar, D., Stevic, Z. ve Sremac, S. (2018a). A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM). Symmetry, 10 (393), 1-22. doi:10.3390/ sym10090393. google scholar
  • Shell, (2020). Shell Helix Ultra Professional AF 5W-30. Erişim tarihi: 20.09.2020, http://tdc.ge/wp-content/ uploads/2014/03/HELIX_ULTRA_PROFESSIONAL_AF_5W-30.pdf. google scholar
  • Sofuoğlu, M. A. (2020). Fuzzy Applications of FUCOM Method in Manufacturing Environment. Politeknik Dergisi, 23(1), 189-195. https://doi.org/10.2339/politeknik.586036. google scholar
  • Total, (2020). Total Quartz 9000 Future NFC 5W-30. Erişim tarihi: 20.09.2020, http://www.lubs-products-database.total.com/gallery/ORIGINALS/visuels/31500/31539. google scholar
  • Zolfani, S. H., Ecer, F., Pamucar, D. ve Raslanas, S. (2020). Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile. International Journal of Strategic Property Management, 24(2), 102-118, https://doi.org/10.3846/ ijspm.2020.11543. google scholar

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DIŞA AKTAR



APA

Genç, V., Özdağoğlu, A., & Keleş, M.K. (2022). Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi. Journal of Transportation and Logistics, 7(1), 55-82. https://doi.org/10.26650/JTL.2022.1020313


AMA

Genç V, Özdağoğlu A, Keleş M K. Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi. Journal of Transportation and Logistics. 2022;7(1):55-82. https://doi.org/10.26650/JTL.2022.1020313


ABNT

Genç, V.; Özdağoğlu, A.; Keleş, M.K. Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi. Journal of Transportation and Logistics, [Publisher Location], v. 7, n. 1, p. 55-82, 2022.


Chicago: Author-Date Style

Genç, Volkan, and Aşkın Özdağoğlu and Murat Kemal Keleş. 2022. “Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi.” Journal of Transportation and Logistics 7, no. 1: 55-82. https://doi.org/10.26650/JTL.2022.1020313


Chicago: Humanities Style

Genç, Volkan, and Aşkın Özdağoğlu and Murat Kemal Keleş. Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi.” Journal of Transportation and Logistics 7, no. 1 (Dec. 2023): 55-82. https://doi.org/10.26650/JTL.2022.1020313


Harvard: Australian Style

Genç, V & Özdağoğlu, A & Keleş, MK 2022, 'Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi', Journal of Transportation and Logistics, vol. 7, no. 1, pp. 55-82, viewed 2 Dec. 2023, https://doi.org/10.26650/JTL.2022.1020313


Harvard: Author-Date Style

Genç, V. and Özdağoğlu, A. and Keleş, M.K. (2022) ‘Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi’, Journal of Transportation and Logistics, 7(1), pp. 55-82. https://doi.org/10.26650/JTL.2022.1020313 (2 Dec. 2023).


MLA

Genç, Volkan, and Aşkın Özdağoğlu and Murat Kemal Keleş. Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi.” Journal of Transportation and Logistics, vol. 7, no. 1, 2022, pp. 55-82. [Database Container], https://doi.org/10.26650/JTL.2022.1020313


Vancouver

Genç V, Özdağoğlu A, Keleş MK. Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi. Journal of Transportation and Logistics [Internet]. 2 Dec. 2023 [cited 2 Dec. 2023];7(1):55-82. Available from: https://doi.org/10.26650/JTL.2022.1020313 doi: 10.26650/JTL.2022.1020313


ISNAD

Genç, Volkan - Özdağoğlu, Aşkın - Keleş, MuratKemal. Otomobil Motor Yağı Alternatiflerinin FUCOM, MAIRCA, MABAC ve BWM Yöntemleri ile Değerlendirilmesi”. Journal of Transportation and Logistics 7/1 (Dec. 2023): 55-82. https://doi.org/10.26650/JTL.2022.1020313



ZAMAN ÇİZELGESİ


Gönderim07.11.2021
Kabul03.01.2022
Çevrimiçi Yayınlanma31.05.2022

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