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Yıl 2022, Cilt: 6 Sayı: 4, 241 - 250, 20.12.2022

Ugur Esme Şeref Öcalır Mustafa Kemal Külekci

https://doi.org/10.26701/ems.1187999

Öz

Kaynakça

  • [1] Ocalir S. The investigation of the effects of welding parameters on mechanical properties and corrosion resistance of joints in friction stir welding of dissimilar materials. MSc Thesis, Tarsus University, Graduate Education Institute, 2018, Tarsus-Turkey.
  • [2] Navale SB, Borkar BR. Process parameters optimization in FSW process using Taguchi method. International Journal of Advance Research and Innovative Ideas Education 2018; 4(4):551-558.
  • [3] Meran C. The joint properties of brass plates by friction stir welding. Materials and Design 2006; 27(9):719-726. https://doi.org/10.1016/j.matdes.2005.05.006.
  • [4] Nandan R, DebRoy T, Bhadeshia HKDH. Recent advances in friction-stir welding-Process, weldment structure and properties. Progress in Materials Science 2008;53:980-1023. https://doi.org/10.1016/j.pmatsci.2008.05.001.
  • [5] Lee WB, Jung SB. The joint properties of copper by friction stir welding. Materials Letters 2004;58(6):1041-1046. https://doi.org/10.1016/j.matlet.2003.08.014.
  • [6] Meran C, Kovan V. Microstructures and mechanical properties of friction stir welded dissimilar copper/brass joints. Materialwissenschaft Und Werkstofftechnik 2008;39(8):521-530. https://doi.org/10.1002/mawe.200800278.
  • [7] Thomas WM, Nicholas ED. Friction stir welding for the transportation industries. Materials & Design 1997;18:269-273. https://doi.org/10.1016/S0261-3069(97)00062-9.
  • [8] Yaroshevsky A. Abundances of chemical elements in the Earth’s crust. Geochemistry International 2006;44(1):48-55. https://doi.org/10.1134/S001670290601006X.
  • [9] Rankin DWH. CRC Handbook of Chemistry and Physics, CRC Press; 2008.
  • [10] http://www.mta.gov.tr/v3.0/bilgi-merkezi/boksit.
  • [11] Sahu PK, Kumari K, Pal S, Pal SK. Hybrid fuzzy-grey-Taguchi based multi weld quality optimization of Al/Cu dissimilar friction stir welded joints. Advances in Manufacturing 2016;4:237–247. https://doi.org/10.1007/s40436-016-0151-8.
  • [12] Sun SJ, Kim JS, Lee WG, Lim JY, Go Y, Kim YM. Influence of friction stir welding on mechanical properties of butt joints of AZ61 magnesium alloy. Advances in Materials Science and Engineering 2017;2017:Article ID 7381403. https://doi.org/10.1155/2017/7381403.
  • [13] Shaik BG, Gowd H, Prasad BD. Investigations on friction stir welding process to optimize the multi responses using GRA method. International Journal of Mechanical Engineering and Technology 2019;10(3):341–352.
  • [14] Prasath S, Vijayan S, Raja DE. Multi Response Optimization of Friction Stir Welding Process Parameters on Dissimilar Magnesium Alloys AZ31 and ZM21 using Taguchi-Based Grey Relation Analysis. La Metallurgia Italiana 2020;8:18-27.
  • [15] Palani K, Elanchezhian C. Multi response Optimization of Friction stir welding process parameters in dissimilar alloys using Grey relational analysis. The 3rd International Conference on Materials and Manufacturing Engineering 2018;390:1-8. https://doi.org/10.1088/1757-899X/390/1/012061.
  • [16] Vijayan S, Raju R, Rao SRK. Multiobjective Optimization of Friction Stir Welding Process Parameters on Aluminum Alloy AA5083 Using Taguchi-Based Grey Relation Analysis. Materials and Manufacturing Processes 2010;25:1206-1212. https://doi.org/10.1080/10426910903536782.
  • [17] Gupta SK, Pandey KN, Kumar R. Multi-Objective Optimization of Friction Stir Welding of Aluminium Alloy Using Grey Relation Analysis with Entropy Measurement Method. Nirma Univeristy Journal of Engineering and Technology 2014;3(1):29-34.
  • [18] Babu KK, Panneerselvam K, Sathiya P, Haq AN, Sundarrajan S, Mastanaiah P, Murthy, CVS. Parameter optimization of friction stir welding of cryorolled AA2219 alloy using artificial neural network modeling with genetic algorithm, International Journal of Advanced Manufacturing Technology, 94 (2018), 3117-3129. https://doi.org/10.1007/s00170-017-0897-6.
  • [19] Yunus M, Alsoufi MS. Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming. Modelling and Simulation in Engineering 2018;1-18.
  • [20] Yousif YK, Daws KM, Kazem BI. Prediction of Friction Stir Welding Characteristic Using Neural Network. Jordan Journal of Mechanical and Industrial Engineering 2008;2(3):151-155.
  • [21] Datta S, Bandyopadhyay A, Kumar PP. Grey-Based Taguchi Method for Optimization of Bead Geometry in Submerged Arc Bead-On-Plate Welding. International Journal of Advanced Manufacturing Technology 2008;39:1136-1143. DOI 10.1007/s00170-007-1283-6.
  • [22] Esme U, Bayramoglu M, Kazancoglu Y, Ozgun S. Optimization of Weld Bead Geometry in Tig Welding Process Using Grey Relation Analysis And Taguchi Method. Materiali in Tehnologije 2009;43(3):143-149.
  • [23] http://referansmetal.com/alasimli-aluminyum/list/4/genel-endustri.
  • [24] http://www.empo.com.tr/aluminyum-lama-ve-cubuk/en-aw-6082.html.

Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis

Yıl 2022, Cilt: 6 Sayı: 4, 241 - 250, 20.12.2022

Ugur Esme Şeref Öcalır Mustafa Kemal Külekci

https://doi.org/10.26701/ems.1187999

Öz

Friction Stir Welding (FSW) which is a kind of solid state welding process used essentially for joining nonferrous metals and their alloys. Involving pollution free and no filler material are the advantages of FSW when compared to other welding methods. The present work was focused on the multi objective optimization of friction stir welded EN AW-6082-T651 and EN AW-5083-H111 aluminum alloys using Taguchi based Grey relational analysis (GRA) method under different parameters of shoulder diameter (SD, mm), tool rotation (TR, rpm) and welding speed (WS, mm/min) on tensile strength (TS, MPa), percent elongation (E, %) and joint efficiency (JE). Taguchi related experiments were performed using L27 Orthogonal Array. The grey relational analysis which relates between the FSW parameters and the responses applied to find the optimum condition. Additionally, the Analysis of Variance (ANOVA) approach was used to identify the most important factor and its impact on the multiple response. The results of the obtained tests were then verified using the confirmation test.

Anahtar Kelimeler

Taguchi method Grey relation analysis Friction stir welding Optimization Tensile strength

Kaynakça

  • [1] Ocalir S. The investigation of the effects of welding parameters on mechanical properties and corrosion resistance of joints in friction stir welding of dissimilar materials. MSc Thesis, Tarsus University, Graduate Education Institute, 2018, Tarsus-Turkey.
  • [2] Navale SB, Borkar BR. Process parameters optimization in FSW process using Taguchi method. International Journal of Advance Research and Innovative Ideas Education 2018; 4(4):551-558.
  • [3] Meran C. The joint properties of brass plates by friction stir welding. Materials and Design 2006; 27(9):719-726. https://doi.org/10.1016/j.matdes.2005.05.006.
  • [4] Nandan R, DebRoy T, Bhadeshia HKDH. Recent advances in friction-stir welding-Process, weldment structure and properties. Progress in Materials Science 2008;53:980-1023. https://doi.org/10.1016/j.pmatsci.2008.05.001.
  • [5] Lee WB, Jung SB. The joint properties of copper by friction stir welding. Materials Letters 2004;58(6):1041-1046. https://doi.org/10.1016/j.matlet.2003.08.014.
  • [6] Meran C, Kovan V. Microstructures and mechanical properties of friction stir welded dissimilar copper/brass joints. Materialwissenschaft Und Werkstofftechnik 2008;39(8):521-530. https://doi.org/10.1002/mawe.200800278.
  • [7] Thomas WM, Nicholas ED. Friction stir welding for the transportation industries. Materials & Design 1997;18:269-273. https://doi.org/10.1016/S0261-3069(97)00062-9.
  • [8] Yaroshevsky A. Abundances of chemical elements in the Earth’s crust. Geochemistry International 2006;44(1):48-55. https://doi.org/10.1134/S001670290601006X.
  • [9] Rankin DWH. CRC Handbook of Chemistry and Physics, CRC Press; 2008.
  • [10] http://www.mta.gov.tr/v3.0/bilgi-merkezi/boksit.
  • [11] Sahu PK, Kumari K, Pal S, Pal SK. Hybrid fuzzy-grey-Taguchi based multi weld quality optimization of Al/Cu dissimilar friction stir welded joints. Advances in Manufacturing 2016;4:237–247. https://doi.org/10.1007/s40436-016-0151-8.
  • [12] Sun SJ, Kim JS, Lee WG, Lim JY, Go Y, Kim YM. Influence of friction stir welding on mechanical properties of butt joints of AZ61 magnesium alloy. Advances in Materials Science and Engineering 2017;2017:Article ID 7381403. https://doi.org/10.1155/2017/7381403.
  • [13] Shaik BG, Gowd H, Prasad BD. Investigations on friction stir welding process to optimize the multi responses using GRA method. International Journal of Mechanical Engineering and Technology 2019;10(3):341–352.
  • [14] Prasath S, Vijayan S, Raja DE. Multi Response Optimization of Friction Stir Welding Process Parameters on Dissimilar Magnesium Alloys AZ31 and ZM21 using Taguchi-Based Grey Relation Analysis. La Metallurgia Italiana 2020;8:18-27.
  • [15] Palani K, Elanchezhian C. Multi response Optimization of Friction stir welding process parameters in dissimilar alloys using Grey relational analysis. The 3rd International Conference on Materials and Manufacturing Engineering 2018;390:1-8. https://doi.org/10.1088/1757-899X/390/1/012061.
  • [16] Vijayan S, Raju R, Rao SRK. Multiobjective Optimization of Friction Stir Welding Process Parameters on Aluminum Alloy AA5083 Using Taguchi-Based Grey Relation Analysis. Materials and Manufacturing Processes 2010;25:1206-1212. https://doi.org/10.1080/10426910903536782.
  • [17] Gupta SK, Pandey KN, Kumar R. Multi-Objective Optimization of Friction Stir Welding of Aluminium Alloy Using Grey Relation Analysis with Entropy Measurement Method. Nirma Univeristy Journal of Engineering and Technology 2014;3(1):29-34.
  • [18] Babu KK, Panneerselvam K, Sathiya P, Haq AN, Sundarrajan S, Mastanaiah P, Murthy, CVS. Parameter optimization of friction stir welding of cryorolled AA2219 alloy using artificial neural network modeling with genetic algorithm, International Journal of Advanced Manufacturing Technology, 94 (2018), 3117-3129. https://doi.org/10.1007/s00170-017-0897-6.
  • [19] Yunus M, Alsoufi MS. Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming. Modelling and Simulation in Engineering 2018;1-18.
  • [20] Yousif YK, Daws KM, Kazem BI. Prediction of Friction Stir Welding Characteristic Using Neural Network. Jordan Journal of Mechanical and Industrial Engineering 2008;2(3):151-155.
  • [21] Datta S, Bandyopadhyay A, Kumar PP. Grey-Based Taguchi Method for Optimization of Bead Geometry in Submerged Arc Bead-On-Plate Welding. International Journal of Advanced Manufacturing Technology 2008;39:1136-1143. DOI 10.1007/s00170-007-1283-6.
  • [22] Esme U, Bayramoglu M, Kazancoglu Y, Ozgun S. Optimization of Weld Bead Geometry in Tig Welding Process Using Grey Relation Analysis And Taguchi Method. Materiali in Tehnologije 2009;43(3):143-149.
  • [23] http://referansmetal.com/alasimli-aluminyum/list/4/genel-endustri.
  • [24] http://www.empo.com.tr/aluminyum-lama-ve-cubuk/en-aw-6082.html.
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliği
Bölüm Research Article
Yazarlar

Ugur Esme 0000-0002-0672-7943

Şeref Öcalır 0000-0003-0123-2295

Mustafa Kemal Külekci 0000-0002-5829-3489

Yayımlanma Tarihi 20 Aralık 2022
Kabul Tarihi 1 Kasım 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 6 Sayı: 4

Kaynak Göster

APA Esme, U., Öcalır, Ş., & Külekci, M. K. (2022). Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis. European Mechanical Science, 6(4), 241-250. https://doi.org/10.26701/ems.1187999
AMA Esme U, Öcalır Ş, Külekci MK. Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis. EMS. Aralık 2022;6(4):241-250. doi:10.26701/ems.1187999
Chicago Esme, Ugur, Şeref Öcalır, ve Mustafa Kemal Külekci. “Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 Using Hybrid Taguchi-Based Grey Relation Analysis”. European Mechanical Science 6, sy. 4 (Aralık 2022): 241-50. https://doi.org/10.26701/ems.1187999.
EndNote Esme U, Öcalır Ş, Külekci MK (01 Aralık 2022) Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis. European Mechanical Science 6 4 241–250.
IEEE U. Esme, Ş. Öcalır, ve M. K. Külekci, “Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis”, EMS, c. 6, sy. 4, ss. 241–250, 2022, doi: 10.26701/ems.1187999.
ISNAD Esme, Ugur vd. “Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 Using Hybrid Taguchi-Based Grey Relation Analysis”. European Mechanical Science 6/4 (Aralık 2022), 241-250. https://doi.org/10.26701/ems.1187999.
JAMA Esme U, Öcalır Ş, Külekci MK. Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis. EMS. 2022;6:241–250.
MLA Esme, Ugur vd. “Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 Using Hybrid Taguchi-Based Grey Relation Analysis”. European Mechanical Science, c. 6, sy. 4, 2022, ss. 241-50, doi:10.26701/ems.1187999.
Vancouver Esme U, Öcalır Ş, Külekci MK. Optimization of Friction Stir Welded Dissimilar Aluminum Alloys EN AW-5083-H111 and EN AW-6082-T651 using Hybrid Taguchi-Based Grey Relation Analysis. EMS. 2022;6(4):241-50.
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