Startseite Mechanical properties of Sr inoculated A356 alloy by Taguchi-based gray relational analysis
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Mechanical properties of Sr inoculated A356 alloy by Taguchi-based gray relational analysis

  • Serdar Osman Yılmaz

    Prof. Dr. Serdar Osman Yılmaz works at Tekirdağ Namık Kemal University, Faculty of Engineering, Department of Mechanical Engineering, Corlu, Tekirdağ, Türkiye. He received his BSc from METU University, Ankara, Faculty of Engineering, Metallurgy and Materials Engineering Department in 1989; his MSc from the Institute of Science and Technology, Metallurgy Department in 1992; and his PhD from the Firat University, Institute of Science and Technology, Metallurgy Department, Elazig in 1998. He studied metal coating techniques, surface modification, welding, casting, and wear.

    , Tanju Teker

    Prof. Dr. Tanju Teker works at Sivas Cumhuriyet University, Faculty of Technology, Department of Manufacturing Engineering, Sivas, Türkiye. He graduated in Metallurgy Education from Gazi University, Ankara, Türkiye, in 1997. He received his MSc and PhD degrees from Firat University, Elazig, Türkiye in 2004 and 2010, respectively. His research interests welding technologies, material process and microstructure control, and material surface treatments.

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    , İbrahim Savaş Dalmış

    Assoc. Prof. Dr. İbrahim Savaş Dalmış works in Tekirdağ Namık Kemal University, Corlu, Tekirdağ in Türkiye. He received his BSc from the Teacher Training in Machine Department, Faculty of Technical Education, University of Marmara, Istanbul, Türkiye, in 1997; his MSc from the Agricultural Machinery of the Institute of Science, University of Trakya, Edirne, Turkey in 2000; and his PhD from the Agricultural Machinery Department, Institute of Science, University of Trakya, Edirne, Türkiye in 2006. His research interests include machine design, mechatronics system design, manufacturing technologies, Cad/Cam systems, tool designs, and welding technologies.

    und Ercan Bulus

    Assoc. Prof. Dr. Ercan Bulus works at the University of Namık Kemal, Faculty of Engineering, Department of Computer Engineering, Corlu, Tekirdağ, Türkiye. He received his BSc from University of Trakya, Edirne, Faculty of Science and Literature, Physics Department in 1988; his MSc from the Trakya University, the Institute of Science and Technology, Physics Department in 1992; and his Ph. D from the Trakya University, Institute of Science and Technology, Department of Computer Engineering, Edirne in 1995. He studied cryptology, computer and network security, and deep learning programming.

Veröffentlicht/Copyright: 1. Juli 2024
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Abstract

In this study, Sr inoculated A356 alloy casted by sand-casting technique. Production parameters such as Sr concentration (wt.%), aging temperature (°C), aging time (h), and constant cooling rate were used. The effect of heat treatment on the microstructure and mechanical features of inoculated A356 materials was examined by using scanning electron microscopy, optical microscopy, and the Taguchi-based gray relational analysis method. The optimum production parameters for A356 alloy were determined as 0.03 Sr concentration, aging 300 °C temperature, and 3 h aging time. Multiple response optimization based on the interaction of these parameters provided a 30.15 % improvement in performance. Gray relational grade (GRG) experimental results showed that the most important parameter was Sr concentration, with a contribution of 76.51 %, according to the analysis by ANOVA statistical method.


Corresponding author: Tanju Teker, Department of Manufacturing Engineering, Faculty of Technology, Sivas Cumhuriyet University, Sivas, Türkiye, E-mail:

About the authors

Serdar Osman Yılmaz

Prof. Dr. Serdar Osman Yılmaz works at Tekirdağ Namık Kemal University, Faculty of Engineering, Department of Mechanical Engineering, Corlu, Tekirdağ, Türkiye. He received his BSc from METU University, Ankara, Faculty of Engineering, Metallurgy and Materials Engineering Department in 1989; his MSc from the Institute of Science and Technology, Metallurgy Department in 1992; and his PhD from the Firat University, Institute of Science and Technology, Metallurgy Department, Elazig in 1998. He studied metal coating techniques, surface modification, welding, casting, and wear.

Tanju Teker

Prof. Dr. Tanju Teker works at Sivas Cumhuriyet University, Faculty of Technology, Department of Manufacturing Engineering, Sivas, Türkiye. He graduated in Metallurgy Education from Gazi University, Ankara, Türkiye, in 1997. He received his MSc and PhD degrees from Firat University, Elazig, Türkiye in 2004 and 2010, respectively. His research interests welding technologies, material process and microstructure control, and material surface treatments.

İbrahim Savaş Dalmış

Assoc. Prof. Dr. İbrahim Savaş Dalmış works in Tekirdağ Namık Kemal University, Corlu, Tekirdağ in Türkiye. He received his BSc from the Teacher Training in Machine Department, Faculty of Technical Education, University of Marmara, Istanbul, Türkiye, in 1997; his MSc from the Agricultural Machinery of the Institute of Science, University of Trakya, Edirne, Turkey in 2000; and his PhD from the Agricultural Machinery Department, Institute of Science, University of Trakya, Edirne, Türkiye in 2006. His research interests include machine design, mechatronics system design, manufacturing technologies, Cad/Cam systems, tool designs, and welding technologies.

Ercan Bulus

Assoc. Prof. Dr. Ercan Bulus works at the University of Namık Kemal, Faculty of Engineering, Department of Computer Engineering, Corlu, Tekirdağ, Türkiye. He received his BSc from University of Trakya, Edirne, Faculty of Science and Literature, Physics Department in 1988; his MSc from the Trakya University, the Institute of Science and Technology, Physics Department in 1992; and his Ph. D from the Trakya University, Institute of Science and Technology, Department of Computer Engineering, Edirne in 1995. He studied cryptology, computer and network security, and deep learning programming.

Acknowledgment

The authors were grateful to Kayalar Copper Industry and Trade Inc. Company for their assistance in conducting the experiments.

  1. Research ethics: Not applicable.

  2. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: No funding was received.

  5. Data availability: Not applicable.

References

[1] Z. M. Shi, Q. Wang, G. Zhao, and R. Y. Zhang, “Effects of erbium modification on the microstructure and mechanical properties of A356 aluminum alloys,” Mater. Sci. Eng. A, vol. 626, pp. 102–107, 2015, https://doi.org/10.1016/j.msea.2014.12.062.Suche in Google Scholar

[2] M. Marzouk, M. Jain, and S. Shankar, “Effect of Sr-modification on the bendability of cast aluminum alloy A356 using digital image correlation method,” Mater. Sci. Eng. A, vol. 598, pp. 277–287, 2014, https://doi.org/10.1016/j.msea.2014.01.011.Suche in Google Scholar

[3] P. Jash, A. W. Nicholls, R. S. Ruoff, and M. Trenary, “Synthesis and characterization of single-crystal strontium hexaboride nanowires,” Nano Lett., vol. 8, no. 11, pp. 3794–3798, 2008, https://doi.org/10.1021/nl8021225.Suche in Google Scholar PubMed

[4] S. Acar and K. A. Guler, “Producing non-dendritic A356 and A380 feedstocks: evaluation of the effects of cooling slope casting parameters,” Mater. Test., vol. 62, no. 11, pp. 1147–1152, 2020, https://doi.org/10.3139/120.111599.Suche in Google Scholar

[5] G. Huiyuan, L. Yanxiang, C. Xiang, and W. Xue, “Effects of boron on eutectic solidification in hypoeutectic Al–Si alloys,” Scr. Mater., vol. 53, no. 1, pp. 69–73, 2005, https://doi.org/10.1016/j.scriptamat.2005.03.011.Suche in Google Scholar

[6] M. Timpel, et al., “The role of strontium in modifying aluminium–silicon alloys,” Acta Mater., vol. 60, no. 9, pp. 3920–3928, 2012, https://doi.org/10.1016/j.actamat.2012.03.031.Suche in Google Scholar

[7] S. M. A. Boutorabi, P. Torkaman, J. Campbell, and A. Zolfaghari, “Structure and properties of carbon steel cast by the ablation process,” Int. J. Metalcast., vol. 15, pp. 306–318, 2021, https://doi.org/10.1007/s40962-020-00466-7.Suche in Google Scholar

[8] E. Heidari, S. M. A. Boutorabi, M. T. Honaramooz, and J. Campbell, “Ablation casting of thin-wall ductile iron,” Int. J. Metalcast., vol. 16, pp. 166–177, 2022, https://doi.org/10.1007/s40962-021-00579-7.Suche in Google Scholar

[9] M. Alipour, B. G. Aghdam, H. E. Rahnoma, and M. Emamy, “Investigation of the effect of Al–5Ti–1B grain refiner on dry sliding wear behavior of an Al–Zn–Mg–Cu alloy formed by strain-induced melt activation process,” Mater. Des., vol. 46, pp. 766–775, 2013, https://doi.org/10.1016/j.matdes.2012.10.058.Suche in Google Scholar

[10] D. Wang, H. Zhang, X. Han, B. Shao, L. Li, and J. Cui, “The analysis of strontium modification on microstructure and mechanical properties of Al-25%Mg2Si in situ composite,” J. Mater. Eng. Perform., vol. 26, pp. 4415–4423, 2017, https://doi.org/10.1007/s11665-017-2889-y.Suche in Google Scholar

[11] S. Tariq, A. Tariq, M. Masud, and Z. Rehman, “Minimizing the casting defects in high-pressure die casting using Taguchi analysis,” Sci. Iran., vol. 29, no. 1, pp. 53–69, 2022, https://doi.org/10.24200/sci.2021.56545.4779.Suche in Google Scholar

[12] T. V. Do and Q. C. Hsu, “Optimization of minimum quantity lubricant conditions and cutting parameters in hard milling of AISI H13 steel,” Appl. Sci., vol. 6, no. 3, p. 83, 2016, https://doi.org/10.3390/app6030083.Suche in Google Scholar

[13] N. P. Vu, et al., “Optimization of grinding parameters for minimum grinding time when grinding tablet punches by CBN wheel on CNC milling machine,” Appl. Sci., vol. 9, no. 5, p. 957, 2019, https://doi.org/10.3390/app9050957.Suche in Google Scholar

[14] T. S. Lan, K. C. Chuang, and Y. M. Chen, “Optimization of machining parameters using fuzzy Taguchi method for reducing tool wear,” Appl. Sci., vol. 8, no. 7, p. 1011, 2018, https://doi.org/10.3390/app8071011.Suche in Google Scholar

[15] M. Azadi Moghaddam and F. Kolahan, “Modeling and optimization of the electrical discharge machining process based on a combined artificial neural network and particle swarm optimization algorithm,” Sci. Iran., vol. 27, no. 3, pp. 1206–1217, 2020, https://doi.org/10.24200/SCI.2019.5152.1123.Suche in Google Scholar

[16] I. Dumanić, S. Jozić, D. Bajić, and J. Krolo, “Optimization of semi-solid high-pressure die casting process by computer simulation, Taguchi method and grey relational analysis,” Int. J. Metalcast., vol. 15, pp. 108–118, 2021, https://doi.org/10.1007/s40962-020-00422-5.Suche in Google Scholar

[17] S. C. Nwafor, S. A. Oke, and C. A. Ayanladun, “Factor analysis approach-Taguchi-Pareto method to casting A356 alloy composite for lightweight wheel rim cover of vehicles,” J. Tek. Ind., vol. 10, no. 1, pp. 31–47, 2022, https://doi.org/10.24912/jitiuntar.v10i1.9407.Suche in Google Scholar

[18] K. C. Apparao and A. K. Birru, “QFD-Taguchi based hybrid approach in die casting process optimization,” Trans. Nonferrous Met. Soc. China, vol. 27, no. 11, pp. 2345–2356, 2017, https://doi.org/10.1016/S1003-6326(17)60260-7.Suche in Google Scholar

[19] W. C. Yang, et al., “Multi-attribute optimization and influence assessment methodology of casting process parameters combined with integrated MADM and Taguchi method,” Int. J. Adv. Manuf. Tech., vol. 129, no. 1, pp. 681–695, 2023, https://doi.org/10.1007/s00170-023-12275-3.Suche in Google Scholar

[20] S. K. Azad, K. Mazloum, H. Khandelwal, N. Gupta, and A. Sata, “Optimization of the process parameters for vertical centrifugal casting of A356 by numerical simulation,” Eng. Res. Express, vol. 6, no. 2, 2024, Art. no. 025403, https://doi.org/10.1088/2631-8695/ad36af.Suche in Google Scholar

[21] S. Gajević, A. Marković, S. Milojević, A. Ašonja, L. Ivanović, and B. Stojanović, “Multi-objective optimization of tribological characteristics for aluminum composite using Taguchi grey and TOPSIS approaches,” Lubricants, vol. 12, no. 5, p. 171, 2024, https://doi.org/10.3390/lubricants12050171.Suche in Google Scholar

[22] T. G. Rajiv, T. S. Reddy, and R. Chandrashekar, “Experimental analysis using Taguchi optimization technique on wear properties of AL-356 alloy MMC reinforced with SiC,” J. Inst. Eng. (India): D, pp. 1–10, 2024, https://doi.org/10.1007/s40033-024-00662-3.Suche in Google Scholar

[23] L. Hengcheng, S. Yu, and S. Guoxiong, “Restraining effect of strontium on the crystallization of Mg2Si phase during solidification in Al-Si-Mg casting alloys and mechanisms,” Mater. Sci. Eng. A, vol. 358, nos. 1–2, pp. 164–170, 2003, https://doi.org/10.1016/S0921-5093(03)00276-4.Suche in Google Scholar

[24] Q. D. Qin, Y. G. Zhao, C. Liu, P. J. Cong, and W. Zhou, “Strontium modification and formation of cubic primary Mg2Si crystals in Mg2Si/Al composite,” J. Alloys Compd., vol. 454, nos. 1–2, pp. 142–146, 2008, https://doi.org/10.1016/j.jallcom.2006.12.074.Suche in Google Scholar

[25] T. Teker, S. O. Yılmaz, and A. Karakoca, “Improvement of metallurgical properties of A356 aluminium alloy by AlCrFeSrTiBSi master alloy,” Mater. Test., vol. 65, no. 2, pp. 224–232, 2023, https://doi.org/10.1515/mt-2022-0407.Suche in Google Scholar

Published Online: 2024-07-01
Published in Print: 2024-09-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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Heruntergeladen am 25.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/mt-2024-0279/html
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