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MIG welding process parameter optimisation of AISI 1026 steel using Taguchi-TOPSIS method
The weld joint quality is greatly influenced by the welding parameters. The right welding parameters must be used in order to get a weld of high quality. In this study, the Taguchi-based TOPSIS method is used to optimize the welding parameters for MIG welding on AISI 1026 mild steel. Welding current, voltage, and wire feed rate are taken as input factors. For the design of experiments, Taguchi's L9 orthogonal array is applied and the MIG welding is carried out on mild steel. The experiments were done to test the hardness and strength of the joints. The specimen gets assigned by TOPSIS based on its performance score. As per the TOPSIS results, specimen 9 has the highest performance score and ranked 1 with process parameters of current, voltage and wire feed rate as 100 amps, 20 V and 2.5 m/min respectively. The analysis of variance (ANOVA) method is used to find the most significant parameter. The optimum parameters for MIG welded butt joint were found as 100 Amp, 20 V and 3 m/min. ANOVA results indicate that current is the most statistically significant factor with a percentage contribution of 68.2% followed by voltage and wire feed rate with 9.15% and 8.95% respectively. With the use of a regression equation, a mathematical model has been developed between the S/N ratio of performance score and process parameters. In order to validate the results, a confirmatory experiment with analysis-optimized parameters has also been carried out. Confirmation results are showing good agreement with the applied approach.
MIG welding process parameter optimisation of AISI 1026 steel using Taguchi-TOPSIS method
The weld joint quality is greatly influenced by the welding parameters. The right welding parameters must be used in order to get a weld of high quality. In this study, the Taguchi-based TOPSIS method is used to optimize the welding parameters for MIG welding on AISI 1026 mild steel. Welding current, voltage, and wire feed rate are taken as input factors. For the design of experiments, Taguchi's L9 orthogonal array is applied and the MIG welding is carried out on mild steel. The experiments were done to test the hardness and strength of the joints. The specimen gets assigned by TOPSIS based on its performance score. As per the TOPSIS results, specimen 9 has the highest performance score and ranked 1 with process parameters of current, voltage and wire feed rate as 100 amps, 20 V and 2.5 m/min respectively. The analysis of variance (ANOVA) method is used to find the most significant parameter. The optimum parameters for MIG welded butt joint were found as 100 Amp, 20 V and 3 m/min. ANOVA results indicate that current is the most statistically significant factor with a percentage contribution of 68.2% followed by voltage and wire feed rate with 9.15% and 8.95% respectively. With the use of a regression equation, a mathematical model has been developed between the S/N ratio of performance score and process parameters. In order to validate the results, a confirmatory experiment with analysis-optimized parameters has also been carried out. Confirmation results are showing good agreement with the applied approach.
MIG welding process parameter optimisation of AISI 1026 steel using Taguchi-TOPSIS method
Int J Interact Des Manuf
Sharma, Swati (author) / Anitha, D. (author) / Chaturvedi, Vedansh (author) / Vimal, Jyoti (author) / Jayaswal, Pratesh (author) / Saxena, Kuldeep K. (author) / Aherwar, Amit (author) / Pathak, Vimal Kumar (author) / Abdullaev, Sherzod Shukhratovich (author)
2024-04-01
13 pages
Article (Journal)
Electronic Resource
English
Metal inert gas arc (MIG) welding , AISI 1026 mid steel , Taguchi method , TOPSIS , S–N ratio , Analysis of variance (ANOVA) Engineering , Engineering, general , Engineering Design , Mechanical Engineering , Computer-Aided Engineering (CAD, CAE) and Design , Electronics and Microelectronics, Instrumentation , Industrial Design
MIG welding process parameter optimisation of AISI 1026 steel using Taguchi-TOPSIS method
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