Multi-Objective Optimization of Skd11 Steel Grinding Process using Entropy and RAM Methods

Grinding is a prevalent method employed for machining products demanding high precision within the mechanical processing industry. This study focuses on the multi-objective optimization of the SKD11 steel grinding process on a surface grinding machine. An experimental procedure, encompassing a total of nine trials, was designed utilizing the Taguchi method. Within each trial, variations were introduced to three cutting parameters: workpiece velocity, feed rate, and depth of cut. Concurrently, measurements were conducted for four objectives, also designated as criteria: surface roughness (Ra), cutting force component along the x-axis (Fx), cutting force component along the y-axis (Fy), and cutting force component along the z-axis (Fz). The ENTROPY method was deployed for the computation of criteria weights, while the RAM method was utilized to resolve the multi-objective optimization problem. The results yielded optimal values for workpiece velocity, feed rate, and depth of cut, corresponding to 10 m/min, 4 mm/stroke, and 0.01 mm, respectively. Associated with these optimal cutting parameter values, the objective values for Ra, Fx, Fy, and Fz were determined to be 0.49 mm, 18.4 N, 15.2 N, and 28.4 N, respectively.

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Publication Details

Journal
European Journal of Engineering and Technology Research
Published
2025-05-10
DOI
https://doi.org/10.24018/ejeng.2025.10.3.3263
Citations
1
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
1.24
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article

Multi-Objective Optimization of Skd11 Steel Grinding Process using Entropy and RAM Methods

Bui Thanh Danh
1 citations
European Journal of Engineering and Technology Research
Manufacturing Process and Optimization
1.24
article

Multi-Objective Optimization of Skd11 Steel Grinding Process using Entropy and RAM Methods

Bui Thanh Danh
article en
1 citations

Abstract

Grinding is a prevalent method employed for machining products demanding high precision within the mechanical processing industry. This study focuses on the multi-objective optimization of the SKD11 steel grinding process on a surface grinding machine. An experimental procedure, encompassing a total of nine trials, was designed utilizing the Taguchi method. Within each trial, variations were introduced to three cutting parameters: workpiece velocity, feed rate, and depth of cut. Concurrently, measurements were conducted for four objectives, also designated as criteria: surface roughness (Ra), cutting force component along the x-axis (Fx), cutting force component along the y-axis (Fy), and cutting force component along the z-axis (Fz). The ENTROPY method was deployed for the computation of criteria weights, while the RAM method was utilized to resolve the multi-objective optimization problem. The results yielded optimal values for workpiece velocity, feed rate, and depth of cut, corresponding to 10 m/min, 4 mm/stroke, and 0.01 mm, respectively. Associated with these optimal cutting parameter values, the objective values for Ra, Fx, Fy, and Fz were determined to be 0.49 mm, 18.4 N, 15.2 N, and 28.4 N, respectively.

European Journal of Engineering and Technology ResearchVol. 10(3)
University of Transport and Communications (VN)
Openalex Percentile: Top 19%
Manufacturing Process and Optimization
1.24
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Multi-Objective Optimization of Skd11 Steel Grinding Process using Entropy and RAM Methods — Bui Thanh Danh · European Journal of Engineering and Technology Research (2025) | TGRS Research Map | TGRS