Selection of natural reinforcement material with multi-criteria decision-making methods for polymer composite materials developed for gun bodies
Year 2023,
Volume: 13 Issue: 4, 911 - 926, 15.10.2023
Yaşam Kandemir
,
Temel Varol
,
Mustafa Aslan
Abstract
Composite materials are engineering materials that have become widespread in the aerospace, defense and automotive sectors due to the improvement of their mechanical, thermal and tribological properties in recent years. One of the most important types of composite materials preferred in the defense industry is polymer composite material. Polymer composite materials are used in the manufacture of light guns due to their high strength, heat and humidity resistance and thermal properties. In order to make these properties more effective, natural fibers are used as reinforcement elements. At this point, it is necessary to proceed to the decision stage in the selection of reinforcement element for polymer composite material in light gun bodies. In this study, the Critic method was used to determine the criterion weights for the selection of materials, and the Topsis, Saw and Marcos methods were used to determine the order of importance for the selection of the most suitable natural reinforcement material. With these applied methods, three different ranking results were calculated and converted into a net ranking with the Board Count method. The correlation between the methods was revealed by using the Spearman correlation coefficient. It has been determined that the most suitable reinforcement for the PA 66 plastic material used in light gun bodies is the banana fiber material. The Young's modulus, which has a criterion weight of 0.180, was determined as the most effective criterion.
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Silah gövdeleri için geliştirilen polimer kompozit malzemeler için çok kriterli karar verme yöntemleri ile doğal takviye malzemesinin seçimi
Year 2023,
Volume: 13 Issue: 4, 911 - 926, 15.10.2023
Yaşam Kandemir
,
Temel Varol
,
Mustafa Aslan
Abstract
Kompozit malzemeler son yıllarda kullanım alanındaki mekanik, termal, tribolojik özelliklerinin iyileştirilmesi sebebiyle havacılık, savunma, otomotiv sektörlerinde kullanımı yaygınlaşan mühendislik malzemeleridir. Kompozit malzemeler içerisinde savunma sektöründe tercih edilen en önemli çeşitlerinden birisi polimer kompozit malzemelerdir. Polimer kompozit malzemeler yüksek mukavemet, ısı ve neme dayanıklılık ve termal özellikleri yönüyle hafif silah imalatında kullanılmaktadır. Bu özelliklerini daha da etkin hale getirmek maksadıyla takviye elemanları olarak doğal elyaflar kullanılmaktadır. Bu noktada, hafif silah gövdelerinde polimer kompozit malzeme için takviye elemanının seçiminde karar aşamasına geçilmesi gerekmektedir. Bu çalışmada malzemelerin seçimi ile ilgili olarak kriter ağırlıklarını belirlemek için Critic yöntemi, malzemelerin en uygun doğal takviye malzemesi seçilebilmesi için önem sıralamalarını belirlemek amacıyla Topsis, Saw ve Marcos yöntemleri ele alınmıştır. Uygulanan bu yöntemler ile üç ayrı sıralama sonucu hesaplanmış ve Borda Sayım yöntemi ile net bir sıralamaya dönüştürülmüştür. Spearman korelasyon katsayısı kullanılarak yöntemler arası ilişki ortaya konulmuştur. Hafif silah gövdelerinde kullanılan PA 66 plastik malzemesi için en uygun takviye muz elyaf malzemesinin olduğu belirlenmiştir. En etkin kriter olarak 0,180 kriter ağırlığına sahip olan Young modülü belirlenmiştir.
Supporting Institution
Tübitak
Thanks
Çalışmanın gerçekleştirilebilmesi için vermiş oldukları katkılar adına Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK), Trabzon Silah Sanayi A.Ş. (TİSAŞ) ve Karadeniz Teknik Üniversitesi’ne teşekkür ederiz. C119073 kodlu ve “Yenilikçi Hafif Silah Teknolojilerinin Geliştirilmesi ve Bu Alana Yönelik Nitelikli Araştırmacıların Yetiştirilmesi” isimli proje, Tübitak 2244 Sanayi Doktora Programı kapsamında Türkiye Bilimsel ve Teknolojik Araştırma Kurumu ve TİSAŞ tarafından desteklenmektedir.
References
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- Amarnath, K., Babu, K.J., & Kumar, M.S. (2022). Comparative analysis of multi criteria decision making techniques for selection of optimal flax fiber reinforced components. Positif Journal, 22(8), 38-50.
Aslan, M. (2012). Characterisation of flax fibers and flax fiber composites being cellulose based sources of materials [Doktora Tezi, Danimarka Teknik Üniversitesi].
- Bhadra, D., & Dhar, N.R. (2022). Selection of the natural fiber for sustainable applications in aerospace cabin interior using fuzzy mcdm model. Materialia, 21, 101270. https://doi.org/10.1016/j.mtla.2021.101270
- Bhardwaj, S., & Sharma, R. (2021). Natural fiber composites: an opportunity for farmers. International Journal of Pure & Applied Bioscience, 5(5), 509-514. https://doi.org/10.18782/2320-7051.5876
- Ecer, F., Böyükaslan, A., & Zolfani, S.H. (2022). Evaluation of cryptocurrencies for investment decisions in the era of industry 4.0: a borda count-based intuitionistic fuzzy set extensions edas-mairca-marcos multi-criteria methodology. Axioms, 11(8), 404. https://doi.org/10.3390/axioms11080404
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- Gurunathan, T., Mohanty, S., & Nayak, S.K. (2015). A review of the recent developments in biocomposites based on natural fibres and their application perspectives. Composites Part A: Applied Science and Manufacturing, 77, 1-25. https://doi.org/10.1016/j.compositesa.2015.06.007
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- Kiruthika, A.V. (2017). A review on physico-mechanical properties of bast fibre reinforced polymer composites. Journal of Building Engineering, 9, 91-99. https://doi.org/10.1016/j.jobe.2016.12.003
- Li, H., Cao, Y., & Su, L. (2022). Pythagorean fuzzy multi-criteria decision-making approach based on spearman rank correlation coefficient. Soft Computing, 26(6), 3001-3012. https://doi.org/10.1007/s00500-021-06615-2
- Mansor, M.R., Sapuan, S.M., Zainudin, E.S., Nuraini, A.A., & Hambali, A. (2013). Hybrid natural and glass fibers reinforced polymer composites material selection using analytical hierarchy process for automotive brake lever design. Materials & Design, 51, 484-492. https://doi.org/10.1016/j.matdes.2013.04.072
- Özçelik, G. (2022). The attitude of mcdm approaches versus the optimization model in finding the safest shortest path on a fuzzy network. Expert Systems with Applications, 203, 117472. https://doi.org/10.1016/j.eswa.2022.117472
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- Raffic, N.M., Babu, K.G., Srinivasan, S., Thirumurugaveerakumar, S., & Kanna, R.B. (2021). Experimental investigation on surface roughness and cutting tool workpiece ınterface temperature for aa6061 using critic and topsis techniques. Materials Today: Proceedings, 47(19), 6858-6863. https://doi.org/10.1016/j.matpr.2021.05.145
- Saba, N., Paridah, M.T., & Jawaid, M. (2015). Mechanical properties of kenaf fibre reinforced polymer composite: a review. Construction and Building Materials, 76, 87-96. https://doi.org/10.1016/j.conbuildmat.2014.11.043
- Sanjay, M.R., Madhu, P., Jawaid, M., Senthamaraikannan, P., Senthil, S., & Pradeep, S. (2018). Characterization and properties of natural fiber polymer composites: a comprehensive review. Journal of Cleaner Production, 172, 566-581. https://doi.org/10.1016/j.jclepro.2017.10.101
- Shaharuzaman, M.A., Sapuan, S.M., Mansor, M.R., & Zuhri, M.Y.M. (2018). Thermoplastic materials selection using vikor method for automotive part. Colloqium of Advanced Materials and Mechanical Engineering Research, 45(2), 75-77.
- Shaharuzaman, M.A., Sapuan, S.M., Mansor, M.R., & Zuhri, M.Y.M. (2019). Decision support strategy in selecting natural fiber materials for automotive side-door impact beam composites. Journal of Renewable Materials, 7(10), 997-1010. https://doi.org/10.32604/jrm.2019.07529
- Singh, K., Rinawa, M.L., Ahamad, N., Chaudhary, V., Das, P.P., Gupta, S., & Gupta, P. (2022). Optimization of tribological performance of natural fibers/epoxy composites using anova & topsis approach. Materials Today: Proceedings, 56(5), 2549-2555. https://doi.org/10.1016/j.matpr.2021.09.112
- Sood, M., & Dwivedi, G. (2018). Effect of fiber treatment on flexural properties of natural fiber reinforced composites: a review. Egyptian Journal of Petroleum, 27(4), 775-783. https://doi.org/10.1016/j.ejpe.2017.11.005
- Spearman, C. (1987). The proof and measurement of association between two things. The American Journal of Psychology, 100, 441-471. https://doi.org/10.2307/1422689
- Stankovic, M., Stevic, Z., Das, D.K., Subotic, M., & Pamucar, D.A. (2020). New fuzzy marcos method for road traffic risk analysis. Mathematics, 8(3), 457. https://doi.org/10.3390/math80304
- Stevic, Z., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new mcdm method: measurement of alternatives and ranking according to compromise solution (marcos). Computers & Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231