Laser welding is widely used for its advantages like deeper weld penetration, narrow heat affected zone, higher welding speeds and better weld quality with less damage to the workpiece compared to arc welding processes. The purpose of this paper is to determine the influence of major laser welding process parameters of beam pulse energy, travel speed and focal position on weld fusion zone geometry in stainless steel and optimizing these parameters to obtain maximum penetration and minimum weld width simultaneously. The experiments were planned according to Taguchi’s L16 orthogonal array. The grey-based Taguchi method was then employed to convert the multiple quality criteria into one single relational grade. Based on the calculated relational grade, Taguchi tools such as analysis of variance and signal-to-noise ratio were used to analyze and obtain the significant parameters and evaluate the optimum combination levels of the mentioned process parameters. Moreover, the effect of optimization procedure was studied on the microstructure and micro-hardness of the weldments. It was concluded that this optimization method can lead to elimination of chain ferrite precipitation and more uniform micro-hardness across the weld bead. The confirmation experiments verified that this method can effectively improve multiple performance characteristics and the results are reproducible in laser welding.
This study has implemented a combined Taguchi method and regression analysis to optimize grinding parameters to enhance the superficial hardness of workpiece. The workpiece material is AISI1045 annealed steel and the process parameters include depth of cut, wheel speed, workpiece speed, cross feed, and mode of dressing. The DOE technique is used to find out the number of experiments by using Taguchi's L27 which includes five parameters (depth of cut, wheel speed, workpiece speed, cross feed, and mode of dressing) at three levels. By applying the mean response and signal to noise ratio (SNR), the best optimal grinding condition has been reached at D3/S3/W2/F2/M1 i.e. depth of cut is 0.03 mm, wheel speed is 32 m/s, workpiece speed is 10 m/min, cross feed is 5 mm/rev, and mode of dressing is fine. Based on the ANOVA, the significance and percentage contribution of each parameter is determined. It has been revealed that depth of cut has maximum contribution on surface hardness. The mathematical model of surface hardness has been developed using regression analysis as a function of the above mentioned independent variables. A confirmation experiment, as final step, has been carried out with 94.5% confidence level to certify optimized result.
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