Research Article


DOI :10.26650/JTL.2024.1149720   IUP :10.26650/JTL.2024.1149720    Full Text (PDF)

3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods

Nihan KabadayıSündüs Dağ

Nowadays, additive manufacturing, also known as three-dimensional (3D) printing, is widely used in many different sectors for both prototyping and part production. 3D printer technologies, which offer more advantages compared with traditional production methods, are applied in a wide range of sectors, from health, education construction, automotive, to food. The utilization of 3D printers offers businesses numerous advantages, including cost reduction, time savings, efficient resource utilization, and the ability to produce customized products. Therefore, selection of 3D printers is a critical decision-making process for businesses. This study discusses the 3D printer selection problem of a furniture parts company located in Kayseri, Turkey. An integrated multicriteria decision making (MCDM) approach, which comprises the fuzzy CRITIC (CRiteria Importance Through Intercriteria Correlation) and fuzzy EDAS (Evaluation based on Distance from Average Solution) methods, is proposed for the solution. In the first stage, weights of 20 subcriteria gathered under the four main criteria (technical, economy, performance, and environment) are determined using the fuzzy CRITIC method. In the second stage, possible four different 3D printer options were determined by the company experts, and all four of these options were ranked using the fuzzy EDAS method. The application results indicated that waste generation (K20) holds significant importance as a criterion in the company’s 3D printer selection process. Waste generation refers to the amount of material discarded or unused during the printing process, which directly impacts both environmental sustainability and production costs. Moreover, the results identified the Flashforge Creator 3 (A1) as the most suitable printer among all the options considered. 

DOI :10.26650/JTL.2024.1149720   IUP :10.26650/JTL.2024.1149720    Full Text (PDF)

Bulanık CRITIC ve Bulanık EDAS Yöntemleri ile 3 Boyutlu Yazıcı Seçimi

Nihan KabadayıSündüs Dağ

Günümüzde katmanlı imalat bir diğer adıyla 3 boyutlu yazıcı çok sayıda farklı sektörde hem prototipleme hem de parça üretimi için yaygın bir şekilde kullanılmaktadır. Geleneksel üretim yöntemlerine göre birçok avantaj sağlayan 3 boyutlu yazıcı teknolojileri sağlık sektöründen eğitim sektörüne ve inşaat, otomotiv sektöründen gıda sektörüne kadar geniş bir yelpazede kendini göstermektedir. 3 boyutlu yazıcıların kullanımı işletmelere maliyet, zaman, kaynak avantajı ve kişiselleştirilmiş ürünler üretme imkânı gibi stratejik avantajlar sunmaktadır. Bu sebeple işletmeler için 3 boyutlu yazıcı seçimi kritik öneme sahip bir karar süreçlerinden biridir.

Bu çalışmada, Kayseri ilinde plastik mobilya aksamları üreten bir firmanın prototipleme ve tasarım amacıyla kullanacakları 3 boyutlu yazıcının seçim problemi ele alınmıştır. Çözüm için Bulanık CRITIC ve bulanık EDAS yöntemlerinden oluşan bütünleşik bir Çok Kriterli Karar Verme Yöntemi (ÇKVV) önerilmiştir. İlk aşamada grup Teknik, Ekonomi, Performans ve Çevre başlıkları altında toplanan 20 farklı kriterin ağırlıkları bulanık CRITIC yöntemi uygulanarak belirlenmiştir. İkinci aşamada, firma yetkilileri tarafından üretimlerine uygun olabilecek dört farklı 3 boyutlu yazıcı belirlenerek, bulanık EDAS yöntemi ile bu alternatif yazıcıların sıralaması gerçekleştirilmiştir. Gerçekleştirilen çalışmanın sonucunda firmanın 3 boyutlu yazıcı seçim kararında en etkili kriterin atık oluşumu (K20) olduğu belirlenmiştir. Bu kriter, 3 boyutlu üretimin baskı sürecinde kullanılmayan veya atılan malzeme miktarını ifade eder. Atık oluşumu, üretim süreçlerinin çevresel sürdürülebilirliğini ve maliyetlerini doğrudan etkilediği için firma için önemlidir. Elde edilen bulgular doğrultusunda, firma için en uygun 3 boyutlu yazıcı modeli Flashforge Creator 3 (A1) olarak belirlenmiştir. Çalışmanın sonucunda belirlenen model ile firmanın prototip üretimi, prototipten ürüne geçiş ve hata tespiti gibi kritik süreçlerde fayda elde etmesi beklenmektedir. 


EXTENDED ABSTRACT


Nowadays, additive manufacturing, also called three-dimensional (3D) printing, is widely used in many different sectors for both prototyping and part production. 3D printer technologies, which offer more advantages compared with traditional production methods, are employed in a wide range of sectors, from health, education, construction, automotive to food. The utilization of 3D printers offers businesses numerous advantages, including cost reduction, time savings, efficient resource utilization, and the ability to produce customized products. Furthermore, the integration of 3D printers into manufacturing operations helps companies develop their local production capabilities. Therefore, 3D printing is anticipated to offer significant flexibility to the global supply chain by enabling companies to quickly adapt to changes in demand or product specifications. For example, if there is a sudden surge in demand for a particular product, manufacturers equipped with 3D printers can swiftly adjust their production schedules and begin manufacturing the required items without the need for retooling or extensive lead times. Additionally, 3D printing enhances resilience within the supply chain by reducing dependency on centralized production facilities and long-distance transportation networks. In the event of disruptions such as natural disasters or geopolitical conflicts affecting traditional manufacturing hubs, companies can utilize local 3D printing capabilities to maintain continuity in production and meet customer demands. This decentralized approach mitigates risks associated with supply chain disruptions and enhances the overall resilience of the global manufacturing ecosystem. In addition, local production with 3D printers in the supply chain helps reduce carbon footprint and decrease transportation costs of finished products, thanks to the more effective use of materials.

As a result, the environmental impact of enterprises during production and distribution processes is diminished, leading to increased efficiency in resource utilization. Consequently, businesses stand to gain from improved sustainable supply chain capabilities. Recently, 3D printers have become a popular tool in the market that can be used for different purposes. The market offers a wide range of 3D printer models with varying functions and print quality across different price ranges. Therefore, selecting the appropriate 3D printer model based on intended use and budget has become a crucial decision for businesses.

The selection of a 3D printer can be considered as a classical multicriteria decision-making (MCDM) problem, as it involves evaluating options against multiple criteria. This study proposes a practical decision-making tool that companies can utilize to select 3D printers suitable for their specific purposes. In addition, a comprehensive list of criteria for 3D printer evaluation is provided to guide companies through the decision-making process of 3D printer selection. An integrated MCDM method, comprising the fuzzy CRITIC (CRiteria Importance Through Intercriteria Correlation) and fuzzy EDAS (Evaluation based on Distance from Average Solution) methods, is suggested for the solution. Criteria weights are determined using the fuzzy CRITIC method, which calculates the importance level of each criterion both objectively and subjectively while processing a large set of criteria. The fuzzy EDAS method, which is a practical method to solve MCDM problems involving many criteria, ranks the alternative 3D printer models. This study contributes to the literature by showing, for the first time, the integrated use of the fuzzy CRITIC and fuzzy EDAS methods for solving 3D printer selection problems. 

This study tests the real-life problem solution performance of the proposed model on a production company located in Kayseri, Turkey. In the first stage, weights of 20 subcriteria gathered under the four main criteria (technical, economy, performance, and environment) are determined via the fuzzy CRITIC method. In the second stage, four different 3D printer models (Flashforge Creator 3, Zortrax M200 Plus, Ultimaker 2+ connect, and Zaxe Z1) are suggested by the company experts; these four options are then ranked using the fuzzy EDAS method. Following this, Flashforge Creator 3 is selected as the most suitable 3D printer model for the company. The feedback collected from the company experts revealed that the company has reaped many benefits in prototype production after it started to utilize the selected 3D printer model. Thanks to the utilization of 3D printers, the company has experienced several advantages, including reduced transition time from prototype to product, early-stage error detection such as during the design process, and the ability to adjust models according to customer needs, consequently improving customer satisfaction.


PDF View

References

  • Adalı, E. A. (2017). CRITIC and MAUT methods for the contract manufacturer selection problem. European Journal of Multidisciplinary Studies, 2(5), 93-101. google scholar
  • Akçakanat, Ö., Aksoy, E., & Teker, T. (2018). CRITIC ve MDL Temelli Edas Yöntemi ile Tr-61 Bölgesi Bankalarinin Performans Değerlendirmesi. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1(32), 1-24. google scholar
  • Ali, J. (2021). A novel score function based CRITIC-MARCOS method with spherical fuzzy information. Computational and Applied Mathe-matics, 40(8), 1-27. google scholar
  • Alipour-Bashary, M., Ravanshadnia, M., Abbasianjahromi, H., & Asnaashari, E. (2021). Building demolition risk assessment by applying a hybrid fuzzy FTA and fuzzy CRITIC-TOPSIS framework. International Journal of Building Pathology and Adaptation. google scholar
  • Asante, D., He, Z., Adjei, N. O., & Asante, B. (2020). Exploring the barriers to renewable energy adoption utilising MULTIMOORA-EDAS method. Energy Policy, 142, 111479. google scholar
  • Ayçin, E. (2020). Personel seçim sürecinde CRITIC ve MAIRCA yöntemlerinin kullanılması. İşletme, 1(1), 1-12. google scholar
  • Aydın, U., & Üstün, A. (2020). Yük taşımacılığı için bulanık EDAS yöntemi ile taşıma modu seçimi. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 3(1), 24-33. google scholar
  • Bai, Y., & Wang, D. (2006). Fundamentals of fuzzy logic control—fuzzy sets, fuzzy rules and defuzzifications. In Advanced fuzzy logic technologies in industrial applications (pp. 17-36). Springer, London. google scholar
  • Bayrakdaroğlu, F. K., & KundakçıI, N. (2019). Bulanık EDAS yöntemi ile arge projesi seçimi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (24), 151-170. google scholar
  • Can, G. F., & Kargı, Ş. (2019). Sektörlerin iş sağlığı ve güvenliği yönünden risk seviyelerinin CRITIC-EDAS entegrasyonu ile değerlendirilmesi. Endüstri Mühendisliği, 30(1), 15-31. google scholar
  • Çetinkaya, C., Kabak, M., & Özceylan, E. (2017). 3D printer selection by using fuzzy analytic hierarchy process and PROMETHEE. Bilişim Teknolojileri Dergisi, 10(4), 371-380 google scholar
  • Chen, T., &Wu, H. C. (2021). Fuzzy collaborative intelligence fuzzy analytic hierarchy process approach for selecting suitable three-dimensional printers. Soft Computing, 25(5), 4121-4134. google scholar
  • Demircan, M. L., & Tunc, S. (2019, July). A proposed service level improvement methodology for public transportation using Interval Type-2 Fuzzy EDAS based on customer satisfaction data. In International Conference on Intelligent and Fuzzy Systems (pp. 1351-1359). Springer, Cham. google scholar
  • Demircioğlu, M., & Coşkun, İ. T. (2018). CRITIC-MOOSRA yöntemi ve UPS seçimi üzerine bir uygulama. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 27(1), 183-195. google scholar
  • Demirtaş, Ö., Zaralı, F., & Doğan S. (2020). Bulanık Ortamda Tedarikçi Seçimi. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 36(3), 456-471. google scholar
  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research, 22(7), 763-770. google scholar
  • Fortune Industry Report. (2021). 3D printing market size, share and Covid-19 impact analysis. (2021) 21 Aralık 2021, https://www.fortunebusinessinsights.com/industry-reports/3d-printing-market-101902. google scholar
  • Feng, X., Wei, C., & Liu, Q. (2018). EDAS method for extended hesitant fuzzy linguistic multi-criteria decision making. International Journal of Fuzzy Systems, 20(8), 2470-2483. google scholar
  • Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., & Antucheviciene, J. (2018). A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering, 18(1), 32-49. google scholar
  • Ghorabaee, M. K., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS method for fuzzy multi-criteria decision-making: an application to supplier selection. International journal of computers communications & control, 11(3), 358-371. google scholar
  • Haleem, A., Khan, S., Luthra, S., Varshney, H., Alam, M., & Khan, M. I. (2021). Supplier evaluation in the context of circular economy: A forward step for resilient business and environment concern. Business Strategy and the Environment, 30(4), 2119-2146. google scholar
  • Huang, Y., Lin, R., & Chen, X. (2021). An enhancement EDAS method based on prospect theory. Technological and Economic Development of Economy, 27(5), 1019-1038. google scholar
  • Jana, C., & Pal, M. (2021). Extended bipolar fuzzy EDAS approach for multi-criteria group decision-making process. Computational and Applied Mathematics, 40(1), 1-15. google scholar
  • Justino Netto, J. M., Ragoni, I. G., Frezzatto Santos, L. E., & Silveira, Z. C. (2019). Selecting low-cost 3D printers using the AHP method: a case study. SN Applied Sciences, 1(4), 1-12. google scholar
  • Kahraman, C., Keshavarz Ghorabaee, M., Zavadskas, E. K., Cevik Onar, S., Yazdani, M., & Oztaysi, B. (2017). Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection. Journal of Environmental Engineering and Landscape Management, 25(1), 1-12. google scholar
  • Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi-criteria supplier selection using fuzzy AHP. Logistics information management. google scholar
  • Kahraman H. (2021). Endüstri 4.0 ile katmanlı imalat. 20 Aralık 2021, https://www.endustri40.com/endustri-4-0-ile-katmanli-uretim/ google scholar
  • Kamali Saraji, M., Streimikiene, D., & Kyriakopoulos, G. L. (2021). Fermatean fuzzy CRITIC-COPRAS method for evaluating the challenges to industry 4.0 adoption for a sustainable digital transformation. Sustainability, 13(17), 9577. google scholar
  • Karagöz, İ., Bekdemir, A. D., & Özlem, T. (2021). 3B yazıcı teknolojilerindeki kullanılan yöntemler ve gelişmeler üzerine bir derleme. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 9(4), 1186-1213. google scholar
  • Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435-451. google scholar
  • Khamhong, P., Yingviwatanapong, C., & Ransikarbum, K. (2019, December). Fuzzy analytic hierarchy process (AHP)-based criteria analysis for 3D printer selection in additive manufacturing. In 2019 Research, Invention, and Innovation Congress (RI2C), (pp. 1-5). IEEE. google scholar
  • Kısa, A. C. G., & Ayçin, E. (2019). OECD Ülkelerinin Lojistik Performanslarının SWARA tabanlı EDAS Yöntemi ile Değerlendirilmesi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 301-325. google scholar
  • Kiracı, K., & Bakır, M. (2018). CRITIC Temelli EDAS Yöntemi ile Havayolu İşletmelerinde Performans Ölçümü Uygulamasi. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (35), 157-174. google scholar
  • Kutlu Gündoğdu, F., Kahraman, C., & Civan, H. N. (2018). A novel hesitant fuzzy EDAS method and its application to hospital selection. Journal of Intelligent & Fuzzy Systems, 35(6), 6353-6365. google scholar
  • Mançanares, C. G., de S Zancul, E., Cavalcante da Silva, J., Cauchick Miguel, P. A. (2015). Additive manufacturing process selection based on parts’ selection criteria. The International Journal of Advanced Manufacturing Technology, 80(5), 1007-1014. google scholar
  • Mishra, A. R., Rani, P., & Pandey, K. (2022). Fermatean fuzzy CRITIC-EDAS approach for the selection of sustainable third-party reverse logistics providers using improved generalized score function. Journal of ambient intelligence and humanized computing, 13(1), 295-311. google scholar
  • Mukul, E., Büyüközkan, G., & Güler, M. (2019). Strategic analysis of intelligent transportation systems. Beykoz Akademi Dergisi, 148-158. google scholar
  • Narayanamoorthy, S., Annapoorani, V., Kang, D., & Ramya, L. (2019). Sustainable assessment for selecting the best alternative of reclaimed water use under hesitant fuzzy multi-criteria decision making. IEEE Access, 7, 137217-137231. google scholar
  • Özbek, A., & Engür, M. (2018). EDAS yöntemi ile lojistik firma web sitelerinin değerlendirilmesi. Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi, 21(2), 417-429. google scholar
  • Özdağoğlu, A., Keleş, M. K., & Eren, F. Y. (2021). Laboratuvar Kan Gazı Cihazı Alternatiflerinin Bulanık VIKOR ve Bulanık EDAS ile Değerlendirilmesi. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 11(1), 220-237. google scholar
  • Polat, G., & Bayhan, H. G. (2020). Selection of HVAC-AHU system supplier with environmental considerations using Fuzzy EDAS method. International Journal of Construction Management, 1-9. google scholar
  • Prabhu, S. R., & Ilangkumaran, M. (2019). Decision making methodology for the selection of3D printer under fuzzy environment. International Journal of Materials and Product Technology, 59(3), 239-252. google scholar
  • Rakhade, R. D., Patil, N. V., Pardeshi, M. R., & Patil, B. G. (2021).Selection of 3D Printer for Innovation Centre of Academic Institution Based on AHP and TOPSIS Methods. Int. J. Res. Appl. Sci. Eng. Technol., vol. 9, no. 12, pp. 1872-1880 google scholar
  • Rakhade, D. (2021). Selection of 3D printer for Innovation Centre of academic institution based on AHP and TOPSIS methods, Int. J. Res. Appl. Sci. Eng. Technol., vol. 9, no. 12, pp. 1872-1880. google scholar
  • Ransikarbum, K., & Khamhong, P. (2021). Integrated fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution for additive manufacturing printer selection. Journal of Materials Engineering and Performance, 30(9), 6481-6492. google scholar
  • Roberson, D. A., Espalin, D., Wicker, R. B. (2013). 3D printer selection: A decision-making evaluation and ranking model. Virtual and Physical Prototyping, 8(3), 201-212. google scholar
  • Shanker, N. (2021). Resiliency-nt-a-revolution-how-3d-printing- will-change-global-supplychains.20 Aralık 2021,https://www.forbes.com/sites/forbestechcouncil/2020/07/08/resiliency-not-a-revolution-how-3d-printing-will-change-global-supply-chains/?sh=36a7310b5b49 google scholar
  • Sönmez, S., Kesen, U. Dalgıç C. 6. 3 Boyutlu yazıcılar uluslararası matbaa teknolojileri sempozyumu, İstanbul, Türkiye, 2018, 471-481. google scholar
  • Stanujkic, D., Popovic, G., & Brzakovic, M. (2018). An approach to personnel selection in the IT industry based on the EDAS method. Transformations in Business & Economics, 17(2), 32-44. google scholar
  • Stanujkic, D., Zavadskas, E. K., Ghorabaee, M. K., & Turskis, Z. (2017). An extension of the EDAS method based on the use of interval grey numbers. Studies in Informatics and Control, 26(1), 5-12. google scholar
  • Stevic, Z., Vasiljevic, M., Zavadskas, E. K., Sremac, S., & Turskis, Z. (2018). Selection of carpenter manufacturer using fuzzy EDAS method. Engineering Economics, 29(3), 281-290. google scholar
  • Tuş, A., & Aytaç Adalı, E. (2019). The new combination with CRITIC and WASPAS methods for the time and attendance software selection problem. Opsearch, 56(2), 528-538. google scholar
  • Ulutaş, A. (2017). EDAS yöntemi kullanılarak bir tekstil atölyesi için dikiş makinesi seçimi. İşletme Araştırmaları Dergisi, 9(2), 169-183. google scholar
  • Ulutaş, A. (2018). Entropi Tabanli Edas Yöntemi ile Lojistik Firmalarinin Performans Analizi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (23), 53-66. google scholar
  • Veskovic, S., Stevic, Z., Karabasevic, D., Rajilic, S., Milinkovic, S., & Stojic, G. (2020). A new integrated fuzzy approach to selecting the best solution for business balance of passenger rail operator: Fuzzy PIPRECIA-fuzzy EDAS model. Symmetry, 12(5), 743. google scholar
  • Wang, S., Wei, G., Lu, J., Wu, J., Wei, C., & Chen, X. (2022). GRP and CRITIC method for probabilistic uncertain linguistic MAGDM and its application to site selection of hospital constructions. Soft Computing, 26(1), 237-251. google scholar
  • Wang, D., & Zhao, J. (2016). Design optimization of mechanical properties of ceramic tool material during turning of ultra-high-strength steel 300M with AHP and CRITIC method. The International Journal of Advanced Manufacturing Technology, 84(9), 2381-2390. google scholar
  • Yang, K., Duan, T., Feng, J., & Mishra, A. R. (2021). Internet of things challenges of sustainable supply chain management in the manufacturing sector using an integrated q-Rung Orthopair Fuzzy-CRITIC-VIKOR method. Journal of Enterprise Information Management. google scholar
  • Rostamzadeh, R., Ghorabaee, M. K., Govindan, K., Esmaeili, A., & Nobar, H. B. K. (2018). Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS-CRITIC approach. Journal of Cleaner Production, 175, 651-669. google scholar
  • Yılmaz, M., & Atan, T. (2021). Hospital site selection using fuzzy EDAS method: case study application for districts of Istanbul. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-12. google scholar
  • Yürüyen, A. A., & Ulutaş, A. (2020). Bulanık AHP ve bulanık EDAS yöntemleri ile üçüncü parti lojistik firması seçimi. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(İktisadi ve İdari Bilimler), 283-294. google scholar
  • Zadeh, L. A. (1996). Fuzzy sets. In Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh (pp. 394-432). google scholar
  • Liu, Y., Eckert, C. M., & Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 161, 113738. google scholar
  • Zagidullin, R., Mitroshkina, T., & Dmitriev, A. (2021, March). Quality function deployment and design risk analysis for the selection and improvement of FDM 3D printer. In IOP Conference Series: Earth and Environmental Science (Vol. 666, No. 6, p. 062123). IOP Publishing. google scholar

Citations

Copy and paste a formatted citation or use one of the options to export in your chosen format


EXPORT



APA

Kabadayı, N., & Dağ, S. (2019). 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods. Journal of Transportation and Logistics, 0(0), -. https://doi.org/10.26650/JTL.2024.1149720


AMA

Kabadayı N, Dağ S. 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods. Journal of Transportation and Logistics. 2019;0(0):-. https://doi.org/10.26650/JTL.2024.1149720


ABNT

Kabadayı, N.; Dağ, S. 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods. Journal of Transportation and Logistics, [Publisher Location], v. 0, n. 0, p. -, 2019.


Chicago: Author-Date Style

Kabadayı, Nihan, and Sündüs Dağ. 2019. “3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods.” Journal of Transportation and Logistics 0, no. 0: -. https://doi.org/10.26650/JTL.2024.1149720


Chicago: Humanities Style

Kabadayı, Nihan, and Sündüs Dağ. 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods.” Journal of Transportation and Logistics 0, no. 0 (May. 2024): -. https://doi.org/10.26650/JTL.2024.1149720


Harvard: Australian Style

Kabadayı, N & Dağ, S 2019, '3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods', Journal of Transportation and Logistics, vol. 0, no. 0, pp. -, viewed 13 May. 2024, https://doi.org/10.26650/JTL.2024.1149720


Harvard: Author-Date Style

Kabadayı, N. and Dağ, S. (2019) ‘3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods’, Journal of Transportation and Logistics, 0(0), pp. -. https://doi.org/10.26650/JTL.2024.1149720 (13 May. 2024).


MLA

Kabadayı, Nihan, and Sündüs Dağ. 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods.” Journal of Transportation and Logistics, vol. 0, no. 0, 2019, pp. -. [Database Container], https://doi.org/10.26650/JTL.2024.1149720


Vancouver

Kabadayı N, Dağ S. 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods. Journal of Transportation and Logistics [Internet]. 13 May. 2024 [cited 13 May. 2024];0(0):-. Available from: https://doi.org/10.26650/JTL.2024.1149720 doi: 10.26650/JTL.2024.1149720


ISNAD

Kabadayı, Nihan - Dağ, Sündüs. 3D Printer Selection by Using Fuzzy CRITIC and Fuzzy EDAS Methods”. Journal of Transportation and Logistics 0/0 (May. 2024): -. https://doi.org/10.26650/JTL.2024.1149720



TIMELINE


Submitted27.07.2022
Accepted27.03.2024
Published Online15.04.2024

LICENCE


Attribution-NonCommercial (CC BY-NC)

This license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.


SHARE




Istanbul University Press aims to contribute to the dissemination of ever growing scientific knowledge through publication of high quality scientific journals and books in accordance with the international publishing standards and ethics. Istanbul University Press follows an open access, non-commercial, scholarly publishing.