Izbor 3D štampača za spojlere trkačkih automobila korišćenjem modela ,,Entropy – CRADIS“
Sažetak
Uvod/cilj: Cilj ovog istraživanja je da identifikuje najprikladniji 3D štammpač za proizvodnju spojlera za trkačke automobile.
Metode: Šesnaest različitih 3D štampača je evaluirano na osnovu osam kriterijuma izbora, uključujući zapreminu štampe, maksimalnu brzinu štampe, debljinu sloja, broj ekstrudera, cenu mašine, cenu filamenta kod proizvođača, maksimalnu temperaturu ekstrudera i maksimalnu temperaturu radne površine. Težine kriterijuma su određene korišćenjem metode Entropy, dok je metoda kompromisnog rangiranja alternativa prema udaljenosti od idealnog rešenja (eng. CRADIS) primenjena za rangiranje mašina i pronalaženje najbolje opcije za proizvodnju spojlera. Za validaciju rezultata sprovedena je analiza osetljivosti korišćenjem različitih metoda.
Rezultati: Ultimaker 2 je identifikovan kao najprikladniji 3D štampač, sledi Delta Non-Turbo WASP 2040, dok UP Plus 2 zauzima najnižu poziciju.
Zaključak: Korišćenjem metoda Entropy i CRADIS, Ultimaker 2 je identifikovan kao 3D štampač sa najboljim performansama. Sledi Delta Non-Turbo WASP 2040, dok je UP Plus 2 rangiran kao najmanje pogodan. Različite višekriterijumske metode odlučivanja (MCDM) su primenjene za poređenje performansi i analizu osetljivosti, dok je Spirmanov koeficijent korelacije rangova korišćen za procenu korelacije između različitih metoda odlučivanja.
Reference
Ansari, A. A & Kamil, M. 2021. Effect of print speed and extrusion temperature on properties of 3D printed PLA using fused deposition modeling process. Materials Today: Proceedings, 45(6), pp.5462-5468. Available at: https://doi.org/10.1016/j.matpr.2021.02.137
Basso, M., Cravero, C., & Marsano, D. 2021. Aerodynamic Effect of the Gurney Flap on the Front Wing of a F1 Car and Flow Interactions with Car Components. Energies, 14(8), 2059. Available at: https://doi.org/10.3390/en14082059
Berman, B., 2012. 3-D printing: The new industrial revolution. Business horizons, 55(2), pp.155-162. Available at: https://doi.org/10.1016/j.bushor.2011.11.003
Buljac, A., Džijan, I., Kozmar, H., Korade, I., & Krizmanić, S. 2016. Automobile aerodynamics influenced by airfoil-shaped rear wing. International Journal of Automotive Technology, 17(3), pp.377–385. Available at: https://doi.org/10.1007/s12239-016-0039-4
Chakraborty, S., Chatterjee, P., & Das, P. P. (2023). Multi-Criteria Decision-Making Methods in Manufacturing Environments: Models and Applications. New York: Apple Academic Press. Avaible at: https://doi.org/10.1201/9781003377030-16
Chang, C. H., Lin, J. J., Lin, J. H., & Chiang, M. C., 2010. Domestic open-end equity mutual fund performance evaluation using extended TOPSIS method with different distance approaches. Expert systems with applications, 37(6), pp.4642-4649. Available at: https://doi.org/10.3846/btp.2017.012
Chatterjee, S., & Chakraborty, S., 2023. A multi-criteria decision-making approach for 3D printer nozzle material selection. Reports in Mechanical Engineering, 4(1), pp.62-79. Available at: https://doi.org/10.31181/rme040121042023c
Eftekhari, H., Al-Obaidi, A. S. M., Eftekhari, S & Ijost, I., 2023. Effect of a Spoiler on the Aerodynamic Performance of a Race Car on Track Using Two Different Turbulence Models. Journal of Design for Sustainable and Environment, 5 (2), pp. 28-37. Available at: https://doi.org/10.17509/ijost. v5i1.22701
Ford, S., & Despeisse, M., 2016. Additive manufacturing and sustainability: An exploratory study of the advantages and challenges. Journal of Cleaner Production, 137, pp.1573-1587. Available at: https://doi.org/10.1016/j.jclepro.2016.04.150
Gangwar, S., Saxena, P., Virmani, N., Biermann, T., Steinnagel, C., & Lachmayer, R. 2024. Selection of a suitable additive manufacturing process for soft robotics application using three-way decision-making. The International Journal of Advanced Manufacturing Technology, 132(3-4), pp.2003-2015. Available at: https://doi.org/10.1007/s00170-024-13398-x
Genç, E., Keleş, M. K., & Özdağoğlu, A. 2024. A hybrid MCDM model for personnel selection based on a novel Gray AHP, Gray MOORA and Gray MAUT methods in terms of business management: An application in the tourism sector. Journal of Decision Analytics and Intelligent Computing, 4(1), pp.263-284. Available at: https://doi.org/10.31181/jdaic10024122024g
Ghorabaee, K, 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), pp.435-451. Available at: https://doi.org/10.15388/Informatica.2015.57
Ghorabaee, K, M., Zavadskas, E. K., Turskis, Z., & Antuchevičienė, J., 2016. A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Available at: https://etalpykla.vilniustech.lt/handle/123456789/116529
Gibson, I., Rosen, D., & Stucker, B., 2015. Additive manufacturing technologies: 3D printing, rapid prototyping, and direct digital manufacturing. Springer. Available at: https://doi.org/10.1007/978-1-4419-1120-9
Guo, N., & Leu, M. C., 2013. Additive manufacturing: Technology, applications and research needs. Frontiers of Mechanical Engineering, 8(3), pp.215-243. Available at: https://doi.org/10.1007/s11465-013-0248-8
Huang, S. H., Liu, P., Mokasdar, A., & Hou, L., 2013. Additive manufacturing and its societal impact: A literature review. International Journal of Advanced Manufacturing Technology, 67(5-8), pp.1191-1203. Available at: https://doi.org/10.1007/s00170-012-4558-5
Jia, Y., He, H., Geng, Y., Huang, B., & Peng, X., 2017. High through-plane thermal conductivity of polymer based product with vertical alignment of graphite flakes achieved via 3D printing. Composites Science and Technology, 145, pp.55-61. Available at: https://doi.org/10.1016/j.compscitech.2017.03.035
Kapetaniou, C., Rieple, A., Pilkington, A., Frandsen, T., & Pisano, P., 2018. Building the layers of a new manufacturing taxonomy: How 3D printing is creating a new landscape of production eco-systems and competitive dynamics. Technological Forecasting and Social Change, 128, pp.22-35. Available at: https://doi.org/10.1016/j.techfore.2017.10.011
Komatina, N. 2025. A Novel BWM-RADAR Approach for Multi-Attribute Selection of Equipment in the Automotive Industry. Spectrum of Mechanical Engineering and Operational Research, 2(1), pp.104-120. Available at: https://doi.org/10.31181/smeor21202531
Kousar, S., Ansar, A., Kausar, N., & Freen, G. 2025. Multi-Criteria Decision-Making for Smog Mitigation: A Comprehensive Analysis of Health, Economic, and Ecological Impacts. Spectrum of Decision Making and Applications, 2(1), pp.53-67. Available at: https://doi.org/10.31181/sdmap2120258
Kumar, R., & Pamucar, D. 2025. A Comprehensive and Systematic Review of Multi-Criteria Decision-Making (MCDM) Methods to Solve Decision-Making Problems: Two Decades from 2004 to 2024. Spectrum of Decision Making and Applications, 2(1), pp.178-197. Available at: https://doi.org/10.31181/sdmap21202524
Katz, J. (2006). Aerodynamics of race cars. Annual Review of Fluid Mechanics, 38, 27-63. Available at: https://doi.org/10.1146/annurev.fluid.38.050304.092016
Khamhong, P., Yingviwatanapong, C., & Ransikarbum, K., 2019. 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. Available at: https://doi.org/10.1109/RI2C48728.2019.8999950
Lai, J., & Chang, Y., 2021. Technology assessment of 3D printing using a two-stage MCDM: case studies on molding industry. International Journal of Innovation Management, 9(1), pp. 53-60. Available at: https://doi.org/10.1007/s00170-012-4558-5
Mardani, A., Jusoh, A., Nor, K., Khalifah, Z., & Zakwan, N., 2015. Multiple criteria decision-making techniques and their applications – A review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28(1), pp.516-571. Available at: https://doi.org/10.1080/1331677X.2015.1075139
Matias, E., & Rao, B., 2015. 3D printing: On its historical evolution and the implications for business. In 2015 Portland International Conference on Management of Engineering and Technology (PICMET), pp. 551-558. IEEE. Available at: https://doi.org/10.1109/PICMET.2015.7273052
Moarefi, A., Sweis, R. J., Hoseini-Amiri, S. M., & AlBalkhy, W. A., 2018. Shannon entropy weighting technique as a practical weighting decision-making tool in project management. International Journal of Management Concepts and Philosophy, 11(4), pp.377-392. Available at: https://doi.org/10.1504/IJMCP.2018.096054
Nagarajan, D., Gobinath, V. M., & Broumi, S., 2023. Multicriteria Decision Making on 3D printers for economic manufacturing using Neutrosophic environment. Neutrosophic Sets and Systems, 57(1), pp.3. Available at: https://digitalrepository.unm.edu/nss_journal/vol57/iss1/3
Nath, D. S., Pujari, P. C., Jain, A., & Rastogi, V. (2021). Drag reduction by application of aerodynamic devices in a race car. Advances in Aerodynamics, 3(1). Available at: https://doi.org/10.1186/s42774-020-00054-7
Pamučar, D., & Ćirović, 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), pp.3016-3028. Available at: https://doi.org/10.1016/j.eswa.2014.11.057
Paul, D., Agarwal, P., Mondal, G., & Banerjee, D., 2015. A comparative analysis of different hybrid MCDM techniques considering a case of selection of 3D printers. Management Science Letters, 5, pp.695-708. Available at: https://doi.org/10.5267/j.msl.2015.5.003
Prabhu, S. R., Ilangkumaran, M., & Mohanraj, T., 2020. 3D Printing of automobile spoilers using MCDM techniques. Materials Testing, 62(11), pp.1121-1125. Available at : https://doi.org/10.3139/120.111592
Puška, A., Stević, Ž. & Pamučar, D., 2022. Evaluation and selection of healthcare waste incinerators using extended sustainability criteria and multi-criteria analysis methods. Environment, Development and Sustainability, 24, pp. 11195-11225. Available at : https://doi.org/10.1007/s10668-021-01902-2
Radovanovic, M., Petrovski, A., Cirkin, E., Behlić, A., Jokic, Z., Chemezov, D., Hashimov, E. G., Bouraima, M. B., & Jana, C. 2024. Application of the new hybrid model LMAW-G-EDAS multi-criteria decision-making when choosing an assault rifle for the needs of the army. Journal of Decision Analytics and Intelligent Computing, 4(1), pp.16-31. Available at: https://doi.org/10.31181/jdaic10021012024r
Raigar, J., Sharma, V. S., Srivastava, S., Chand, R., & Singh, J. 2020. A decision support system for the selection of an additive manufacturing process using a new hybrid MCDM technique. Sādhanā, 45, pp. 1-14. Available at: https://doi.org/10.1007/s12046-020-01338-w
Rayna, T., & Striukova, L., 2016. From rapid prototyping to home fabrication: How 3D printing is changing business model innovation. Technological forecasting and social change, 102, pp.214-224. Available at: https://doi.org/10.1016/j.techfore.2015.07.023
Sahoo, S. K., Choudhury, B. B., Dhal, P. R., & Hanspal, M. S. 2025. A Comprehensive Review of Multi-criteria Decision-making (MCDM) Toward Sustainable Renewable Energy Development. Spectrum of Operational Research, 2(1), pp.268-284. Available at: https://doi.org/10.31181/sor21202527
Sandström, C. G., 2016. The non-disruptive emergence of an ecosystem for 3D Printing - Insights from the hearing aid industry's transition 1989 - 2008. Technological Forecasting and Social Change, 102, pp.160-168. Available at: https://doi.org/10.1016/j.techfore.2015.09.006
Sellamuthu, P., Kalita, K., Kumar, A., Chohan, J. S., Rathee, S., & Sharma, Y. K. (2024, December). A hybrid Merec-Mabac approach for 3D printer nozzle material selection. In AIP Conference Proceedings. 3217(1). Available at: https://doi.org/10.1063/5.0234604
Shannon, C. E., 1948. A mathematical theory of communication. The Bell System Technical Journal, 27(3), pp. 379-423. Available at: https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Tesic, D., & Marinkovic, D. 2023. Application of fermatean fuzzy weight operators and MCDM model DIBR-DIBR II-NWBM-BM for efficiency-based selection of a complex combat system. Journal of Decision Analytics and Intelligent Computing, 3(1), pp.243–256. Available at: https://doi.org/10.31181/10002122023t
Tomelleri, F., Bosetti, P., & Brunelli, M. 2025. Optimizing 3D printer selection through multi-criteria decision analysis. The International Journal of Advanced Manufacturing Technology, 139(7-8), pp. 3871-3890. Available at: https://doi.org/10.1007/s00170-025-16148-9
Vinodh, S., & Shinde, P., 2018. Parametric optimization of 3D printing process using MCDM method. In Precision Product-Process Design and Optimization: Select Papers from AIMTDR 2016, pp. 141-159. Available at: https://doi.org/10.1007/978-981-10-8767-7_6
Wang, W., Wang, Y., Fan, S., Han, X., Wu, Q., & Pamucar, D., 2022. A complex spherical fuzzy CRADIS method based Fine-Kinney framework for occupational risk evaluation in natural gas pipeline construction. Journal of Petroleum Science and Engineering, 220, 111246. https://doi.org/10.1016/j.petrol.2022.111246
Wang, Y. C., Chen, T., & Lin, Y. C., 2023. 3D Printer Selection for Aircraft Component Manufacturing Using a Nonlinear FGM and Dependency-Considered Fuzzy VIKOR Approach. Aerospace, 10(7), pp. 591. Available at: https://doi.org/10.3390/aerospace10070591
Wang, Y., Zhong, R. Y., & Xu, X., 2018. A decision support system for additive manufacturing process selection using a hybrid multiple criteria decision-making method. Rapid Prototyping Journal, 24(9), pp. 1544-1553. Available at: https://doi.org/10.1108/RPJ-01-2018-0002
West, J., & Kuk, G., 2016. The complementarity of openness: How MakerBot leveraged Thingiverse in 3D printing. Technological Forecasting and Social Change, 102, pp.169-181. Available at: https://doi.org/10.1016/j.techfore.2015.07.025
Więckowski, J., & Sałabun, W. 2025. Comparative Sensitivity Analysis in Composite Material Selection: Evaluating OAT and COMSAM Methods in Multi-criteria Decision-making. Spectrum of Mechanical Engineering and Operational Research, 2(1), pp.1-12. Available at: https://doi.org/10.31181/smeor21202524
Wohlers, T., Gornet, T., Mostow, N., Campbell, I., Diegel, O., Kowen, J., & Peels, J., 2016. History of additive manufacturing. Available at: http://dx.doi.org/10.2139/ssrn.4474824
Yalçın, G. C., Kara, K., & Özyürek, H. 2025. Evaluating Financial Performance of Companies in the Borsa Istanbul Sustainability Index Using the CRITIC-MABAC Method. Spectrum of Operational Research, 2(1), pp.323-346. Available at: https://doi.org/10.31181/sor21202530
Yeh, C. C., & Chen, Y. F., 2018. Critical success factors for adoption of 3D printing. Technological Forecasting and Social Change, 132, pp. 209-216. Available at: https://doi.org/10.1016/j.techfore.2018.02.003
Yildirim, B., & Ayyildiz, E. (2025). Selecting the most suitable 3D printing technology for custom manufacturing using fuzzy decision-making methodology. International Journal on Interactive Design and Manufacturing. Available at : https://doi.org/10.1007/s12008-025-02258-x
Yushuo, C., & Ling, D. 2024. A Framework for Assessment of Logistics Enterprises’ Safety Standardization Performance Based on Prospect Theory. Journal of Operations Intelligence, 2(1), pp.153-166. Available at: https://doi.org/10.31181/jopi21202418
Zavadskas, E. K., Turskis, Z., & Kildienė, S., 2014. State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), pp.165-179. Available at: https://doi.org/10.3846/20294913.2014.892037
Zeleny, M. (Ed.)., 2012. Multiple criteria decision-making Kyoto 1975 (Vol. 123). Springer Science & Business Media, 123. Available at: https://doi.org/10.1007/978-3-642-45486-8
Zhang, S., & Esangbedo, M. O., 2025. Urban Scenic Spot Activity Center Investment: Strategic Construction Company Selection Using the Grey System-II Thinking Compromise Ranking of Alternatives from Distance to Ideal Solution Multi-Criteria Decision-Making Method. Systems, 13(1), 67. Available at: https://doi.org/10.3390/systems13010067
Zhang, X., Toet, W., & Zerihan, J., 2006. Ground effect aerodynamics of race cars. Applied Mechanics Reviews, 59(1), pp.33-49. Available at: https://doi.org/10.1115/1.2110263
Sellamuthu, P., Kalita, K., Kumar, A., Chohan, J. S., Rathee, S., & Sharma, Y. K. (2024, December). A hybrid Merec-Mabac approach for 3D printer nozzle material selection. In AIP Conference Proceedings. 3217(1). Available at: https://doi.org/10.1063/5.0234604
https://support.makerbot.com/s/article/1667337895715 Date of accession: 15th december 2024
https://www.3dwasp.com/en/delta-printer-delta-wasp-2040/ Date of accession: 15th december 2024
https://www.treatstock.com/machines/item/342-up-plus-2 Date of accession: 16th december 2024
Sva prava zadržana (c) 2026 Rajeev Ranjan, Sonu Rajak, PRASENJIT CHATTERJEE
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