Using Taguchi Grey Relational Analysis Multi-Object of Process Parameters in Electric Resistance Welding of Wire to Recovery AISI1045 Steell Shaft

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This study focuses on the multi-objective optimization of the welding joint of AISI 1045 steel shafts with AISI 1070 filler wire 1.8 mm in diameter by electric resistance welding method. During the welding process, welding parameters input are important because it determines the quality of the welding joint. Therefore, in this study, Taguchi method was used in combination with grey relational analysis to select the welding parameters suitable for this welding process. The experiments were performed according to the orthogonal array L9 designed by the Taguchi method. The input welding mode parameters used in this study include welding current (Ih), force (F), welding speed (Vh). The output characteristics for the selected weld quality target are minimum tensile strength and micro hardness. Grey analyzes were conducted to optimize for the input parameters, the analysis results show that the set of input parameters suitable for the output quality are Ih = 7.5 KA; F = 1.7 KN; Vh = 1.5 cm/s. This is followed by the process of assessing the significance of the factors to all qualities of the welded joint using the ANOVA analysis process.

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39-44

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January 2021

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© 2021 Trans Tech Publications Ltd. All Rights Reserved

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[1] S. Datta, A. Bandyopadhyay, P. K. Pal, Grey-based Taguchi method for optimization of bead geometry in submerged arc bead-on-plate welding, Int. J. Adv. Manufact. Technol. 39 (2008) 1136-1143.

DOI: 10.1007/s00170-007-1283-6

Google Scholar

[2] A. K. Srirangan, S. Paulraj, Multi-response optimization of process parameters for TIG welding of Incoloy 800HT by Taguchi grey relational analysis, Eng. Sci. Technol. Int. J. 19(2) (2016) 811-817.

DOI: 10.1016/j.jestch.2015.10.003

Google Scholar

[3] N. Ghosh, P. K. Pal, G. Nandi, Parametric optimization of MIG welding on 316L austenitic stainless steel by Grey-Based Taguchi method, Procedia Technol. 25 (2016) 1038-1048.

DOI: 10.1016/j.protcy.2016.08.204

Google Scholar

[4] P. K. Sahu, S. Pal, Multi-response optimization of process parameters in friction stir welded AM20 magnesium alloy by Taguchi grey relational analysis, J. Magnesium Alloys, 3(1) (2015) 36-46.

DOI: 10.1016/j.jma.2014.12.002

Google Scholar

[5] M. T. Nguyen, V. N. Nguyen, S.-C. Huang, Optimizing resistance welding parameters on adhesion strength of C45 steel shaft by using Taguchi method, in J. Physics Conf. Ser. 1303 (2019) 012148.

DOI: 10.1088/1742-6596/1303/1/012148

Google Scholar

[6] M. Ortiz, J. Ovejero-Garcia, Effect of hydrogen on Young's modulus of AISI 1005 and 1070 steels, J. Mater. Sci. 27 (1992) 6777-6781.

DOI: 10.1007/bf01165968

Google Scholar