Optimization of machining parameters during the ECCDG of inconel 718 using PCA based grey relational analysis

Yadav, Sunil Kumar; Yadav, Sanjeev Kumar Singh

doi:10.1016/j.matpr.2020.02.557

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…According to the gray relational analysis (GRA) [21][22][23][24][25], the grey relational coefficient ( ) of Vi and V with respect to the j-th index is: ( where, β is the identification coefficient, its value generally takes β=0.5.…”

Section: Minimizingmentioning

confidence: 99%

Enhancement Strategies for Classroom Teaching Effect of Professional Art Education

2021

Int. J. Emerg. Technol. Learn.

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In professional art education, it is a great challenge to improve the classroom teaching effect. To cope with the challenge, this paper identifies the factors affecting the classroom teaching effect of professional art education from the perspective of teachers and that of students, through multi-perspective analysis. In the context of professional art education, the connotations of enhancing the classroom teaching effect were fully analyzed. On this basis, several strategies were put forward to enhance the said effect in professional art education. In addition, multi-angled measurement index systems were established for the enhancement, and a measurement model for the said effect was created through multi-factor decision-making. The research findings provide strong practical and theoretical supports to improving the classroom teaching effect of professional art education.

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Section: Minimizingmentioning

confidence: 99%

Enhancement Strategies for Classroom Teaching Effect of Professional Art Education

2021

Int. J. Emerg. Technol. Learn.

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Effect of water-emulsive biodiesel/diesel blend with alumina nanoparticles on diesel engine performance and emissions: experiments and optimization

Khidr,

Hassan,

Megahed

et al. 2024

Process Safety and Environmental Protection

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Optimization of Cutting Parameters for Milling Enset Fiber Reinforced Epoxy Composite

Muche¹,

Workneh

Zewge³

2023

Preprint

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Machining of composite materials is accompanied by sever challenges. Fiber pullouts, fiber breakages, delamination of laminates, matrix burnings are some of the challenges, which brings significant quality and performance reductions of the product. These challenges able to be reduced with controlled or optimized machining parameters. This study investigates the optimization of cutting parameters for end milling of enset fiber reinforced epoxy composite materials to obtain optimum surface roughness and material removal rate simultaneously. The experimental runs designed based on Taguchi L9 (33 ) orthogonal arrays. The influence of cutting parameters is determined by the analysis of variance (ANOVA). Optimization is performed by coupling grey relational analysis and principal component analysis. The results revealed that depth of cut has greater contributions followed by spindle speed and feed rate respectively on the gray relational grades (GRG). The optimum values of surface roughness and material removal rate were obtained at spindle speed of 1000rpm, feed rate of 300mm/min and depth of cut of 1.5mm.

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Optimization of machining parameters during the ECCDG of inconel 718 using PCA based grey relational analysis

Cited by 3 publications

References 13 publications

Enhancement Strategies for Classroom Teaching Effect of Professional Art Education

Enhancement Strategies for Classroom Teaching Effect of Professional Art Education

Effect of water-emulsive biodiesel/diesel blend with alumina nanoparticles on diesel engine performance and emissions: experiments and optimization

Optimization of Cutting Parameters for Milling Enset Fiber Reinforced Epoxy Composite

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