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Çok Kriterli Karar Verme Yöntemlerini Kullanarak Metal Eklemeli Üretim için Malzeme Seçimi

Year 2024, Volume: 6 Issue: 3, 151 - 161, 26.10.2024
https://doi.org/10.47933/ijeir.1525040

Abstract

Eklemeli imalat, geleneksel imalat yöntemlerine göre birçok avantajından dolayı son yıllarda birçok endüstride yaygın bir kullanım alanı bulan yeni nesil imalat yöntemi olarak dikkatleri üzerinde toplamaktadır. Metal eklemeli imalatta teknolojisinde kullanılan malzemeler oldukça geniş bir yelpazeye sahiptir. Dolayısıyla bu tercih edilebilir malzemeler arasından ideal seçimi yapmak oldukça önemlidir. Malzeme seçim süreçlerinde çok kriterli karar verme (MCDM) teknikleri güvenilir ve etkili yöntemlerdendir ve malzeme seçim süreçlerinde etkin bir şekilde kullanılmaktadır. Bu çalışmada metal eklemeli imalat için farklı kriterler ve malzemeler arasından seçim sürecine TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) ve Additive Ratio Assessment (ARAS) yöntemleri uygulanmıştır. TOPSIS yönteminde ilk sırayı AlSi12Cu2Fe malzeme alırken ARAS yönteminde ise H13 malzemenin aldığı görülmüştür. İkinci sırayı ise TOPSIS yönteminde H13 malzeme alırken ARAS yönteminde ise AlSi12Cu2Fe malzemenin aldığı tespit edilmiştir. TOPSIS ve ARAS yöntemleri arasında 0.977 Pearson korelasyon katsayısı ile güçlü bir ilişki olduğu belirlenmiştir. TOPSIS ve ARAS yöntemlerinde ilk iki sırayı alan malzemelerin eklemeli imalatta kullanılmasında, teknolojik uygulamanın niteliğine göre karar verilmesinin daha etkili olacağı sonucuna varılmıştır.

References

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  • [24] Zavadskas, E. K., Turskis, Z., & Vilutiene, T. (2010). Multiple criteria analysis of foundation instalment alternatives by applying the Additive Ratio Assessment (ARAS) method. Archives of Civil and Mechanical Engineering, 10(3), 123-141.
  • [25] Liu, Y., Mu, Y., Chen, K., Li, Y., & Guo, J. (2020). Daily activity feature selection in smart homes based on pearson correlation coefficient. Neural Processing Letters, 51, 1771-1787.
  • [26] Özakin, B. (2023). A comparative study of the selection of cutting fluids used in machining processes by multi criteria decision making (MCDM) methods. Sādhanā, 48(4), 204.
  • [27] Pezda, J. (2010). Heat treatment of EN AC-AlSi13Cu2Fe silumin and its effect on change of hardness of the alloy. Archives of Foundry Engineering, 10(1), 131-134.
  • [28] Du, X., Liu, X., Shen, Y., Liu, R., & Wei, Y. (2023). H13 tool steel fabricated by wire arc additive manufacturing: Solidification mode, microstructure evolution mechanism and mechanical properties. Materials Science and Engineering: A, 883, 145536.

Material Selection for Metal Additive Manufacturing Using Multi-Criteria Decision Making Methods

Year 2024, Volume: 6 Issue: 3, 151 - 161, 26.10.2024
https://doi.org/10.47933/ijeir.1525040

Abstract

Additive manufacturing has attracted attention as a new generation manufacturing method that has found widespread use in many industries in recent years due to its many advantages over traditional manufacturing methods. The materials used in metal additive manufacturing technology have a wide range. Therefore, making the ideal choice among these preferable materials is very important. Multi-criteria decision making (MCDM) techniques are reliable and effective methods in material selection processes and are effectively used in material selection processes. In this study, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Additive Ratio Assessment (ARAS) methods were applied to the selection process among different criteria and materials for metal additive manufacturing. It was observed that AlSi12Cu2Fe material ranked first in the TOPSIS method, while H13 material ranked first in the ARAS method. The second place was taken by H13 material in the TOPSIS method and AlSi12Cu2Fe material in the ARAS method. A strong relationship exists between TOPSIS and ARAS methods with a Pearson correlation coefficient of 0.977. It has been concluded that it will be more effective to decide according to the nature of the technological application in the use of the materials that rank first two in TOPSIS and ARAS methods in additive manufacturing.

References

  • [1] Gao, W., Zhang, Y., Ramanujan, D., Ramani, K., Chen, Y., Williams, C. B., ... & Zavattieri, P. D. (2015). The status, challenges, and future of additive manufacturing in engineering. Computer-Aided Design, 69, 65-89.
  • [2] Kadkhoda-Ahmadi, S., Hassan, A., & Asadollahi-Yazdi, E. (2019). Process and resource selection methodology in design for additive manufacturing. The International Journal of Advanced Manufacturing Technology, 104, 2013-2029.
  • [3] Cooke, S., Ahmadi, K., Willerth, S., & Herring, R. (2020). Metal additive manufacturing: Technology, metallurgy and modelling. Journal of Manufacturing Processes, 57, 978-1003.
  • [4] Gu, D., Shi, X., Poprawe, R., Bourell, D. L., Setchi, R., & Zhu, J. (2021). Material-structure-performance integrated laser-metal additive manufacturing. Science, 372(6545), eabg1487.
  • [5] Bourell, D., Kruth, J. P., Leu, M., Levy, G., Rosen, D., Beese, A. M., & Clare, A. (2017). Materials for additive manufacturing. CIRP Annals, 66(2), 659-681.
  • [6] Vaneker, T., Bernard, A., Moroni, G., Gibson, I., & Zhang, Y. (2020). Design for additive manufacturing: Framework and methodology. CIRP Annals, 69(2), 578-599.
  • [7] Qin, Y., Qi, Q., Shi, P., Scott, P. J., & Jiang, X. (2023). Selection of materials in metal additive manufacturing via three-way decision-making. The International Journal of Advanced Manufacturing Technology, 126(3), 1293-1302.
  • [8] Uz Zaman, U. K., Rivette, M., Siadat, A., & Mousavi, S. M. (2018). Integrated product-process design: Material and manufacturing process selection for additive manufacturing using multi-criteria decision making. Robotics and Computer-Integrated Manufacturing, 51, 169-180.
  • [9] Agrawal, R. (2021). Sustainable material selection for additive manufacturing technologies: A critical analysis of rank reversal approach. Journal of Cleaner Production, 296, 126500.
  • [10] Wang, Y., Blache, R., & Xu, X. (2017). Selection of additive manufacturing processes. Rapid Prototyping Journal, 23(2), 434-447.
  • [11] Mahapatra, S. S., & Panda, B. N. (2013). Benchmarking of rapid prototyping systems using grey relational analysis. International Journal of Services and Operations Management, 16(4), 460-477.
  • [12] Kek, V., Vinodh, S., Brajesh P. & Muralidharan, R. (2016). Rapid prototyping process selection using multi criteria decision making considering environmental criteria and its decision support system. Rapid Prototyping Journal, 22(2), 225-250.
  • [13] Alghamdy, M., Ahmad, R., & Alsayyed, B. (2019). Material selection methodology for additive manufacturing applications. Procedia CIRP, 84, 486-490.
  • [14] Palanisamy, M., Pugalendhi, A., & Ranganathan, R. (2020). Selection of suitable additive manufacturing machine and materials through–the best-worst method (BWM). The International Journal of Advanced Manufacturing Technology, 107, 2345-2362.
  • [15] 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, 1-14.
  • [16] Malaga, A. K., Agrawal, R., & Wankhede, V. A. (2022). Material selection for metal additive manufacturing process. Materials Today: Proceedings, 66, 1744-1749.
  • [17] Chandra, M., Shahab, F., Kek, V., & Rajak, S. (2022). Selection for additive manufacturing using hybrid MCDM technique considering sustainable concepts. Rapid Prototyping Journal, 28(7), 1297-1311.
  • [18] Qin, Y., Qi, Q., Shi, P., Scott, P. J., & Jiang, X. (2023). Selection of materials in metal additive manufacturing via three-way decision-making. The International Journal of Advanced Manufacturing Technology, 126(3), 1293-1302.
  • [19] Srinivas, M. N., & Vimal, K. E. K. (2023). Benchmarking the metal additive manufacturing processes using integrated AHP-PROMETHEE approach. International Journal of Process Management and Benchmarking, 15(3), 332-358.
  • [20] Junaid, M., uz Zaman, U. K., Naseem, A., Ahmad, Y., & Aqeel, A. B. (2024). Material Selection in Additive Manufacturing for Aerospace Applications using Multi-Criteria Decision Making. In MATEC Web of Conferences (Vol. 398, p. 01012). EDP Sciences.
  • [21] Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple Attribute Decision Making (pp. 58-191). Springer, Berlin, Heidelberg.
  • [22] Alptekin, N. (2013). Integration of SWOT analysis and TOPSIS method in strategic decision making process. The Macrotheme Review, 2(7), 1-8.
  • [23] Zavadskas, E. K., & Turskis, Z. (2010). A new additive ratio assessment (ARAS) method in multicriteria decision‐making. Technological and Economic Development of Economy, 16(2), 159-172.
  • [24] Zavadskas, E. K., Turskis, Z., & Vilutiene, T. (2010). Multiple criteria analysis of foundation instalment alternatives by applying the Additive Ratio Assessment (ARAS) method. Archives of Civil and Mechanical Engineering, 10(3), 123-141.
  • [25] Liu, Y., Mu, Y., Chen, K., Li, Y., & Guo, J. (2020). Daily activity feature selection in smart homes based on pearson correlation coefficient. Neural Processing Letters, 51, 1771-1787.
  • [26] Özakin, B. (2023). A comparative study of the selection of cutting fluids used in machining processes by multi criteria decision making (MCDM) methods. Sādhanā, 48(4), 204.
  • [27] Pezda, J. (2010). Heat treatment of EN AC-AlSi13Cu2Fe silumin and its effect on change of hardness of the alloy. Archives of Foundry Engineering, 10(1), 131-134.
  • [28] Du, X., Liu, X., Shen, Y., Liu, R., & Wei, Y. (2023). H13 tool steel fabricated by wire arc additive manufacturing: Solidification mode, microstructure evolution mechanism and mechanical properties. Materials Science and Engineering: A, 883, 145536.
There are 28 citations in total.

Details

Primary Language English
Subjects Optimization Techniques in Mechanical Engineering
Journal Section Research Articles
Authors

Batuhan Özakın 0000-0003-1754-949X

Kürşat Gültekin 0000-0002-6790-6822

Early Pub Date October 26, 2024
Publication Date October 26, 2024
Submission Date July 30, 2024
Acceptance Date October 8, 2024
Published in Issue Year 2024 Volume: 6 Issue: 3

Cite

APA Özakın, B., & Gültekin, K. (2024). Material Selection for Metal Additive Manufacturing Using Multi-Criteria Decision Making Methods. International Journal of Engineering and Innovative Research, 6(3), 151-161. https://doi.org/10.47933/ijeir.1525040

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