The use of Taguchi method to optimize the laser welding of sealing neuro-stimulator

Parameters optimization for friction spot welding of AZ31 magnesium alloy by Taguchi method

“…F-test is based on comparing model and residual variances through the ratio between the model mean square and the residual or error mean square. F-value is close to one when the variance values are similar, which means a low effect of the parameter on the response, whereas high F-value indicates a significant effect [5]. P% is a function of sum of squares and indicates the relative power of each parameter to reduce the total variation [6,7].…”

“…The level of larger S/N ratio is the optimal process parameter one. Analysis of variance (ANOVA) is performed to investigate which parameters have a significant effect on the quality characteristic [5,6].…”

Welding process selection for repairing nodular cast iron engine block by integrated fuzzy data envelopment analysis and TOPSIS approaches

“…Considering (10), (18) and (20) and after linearization, fuzzy Model (17) is transformed to the following three linear models.…”

“…Garcı'a-Allende et al [19] proposed an approach combined of feature selection and artificial neural networks to monitor the quality of arc-welding process. Xiansheng et al [20] optimized the laser welding of sealing neuro-simulator via Taguchi method. Meran [21] used the genetic algorithm to optimize welding parameter for joined brass plates.…”

Application of Taguchi and FEM to Explore the Surface Properties of Glass Using USM Process

“…The robust design of flank milling parameters based on grey-taguchi method was reported [4]. The effects of the Nd: YAG laser welding parameters on the bead formation on the neuro-stimulator were analysed by [5]. The effects of magnetic force on EDM machining characteristics were explored using L 18 orthogonal array based on taguchi method and statistically evaluated the experimental data by analysis of variance (ANOVA).…”