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

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  • Bui Thanh Danh

    (University of Transport and Communications, Vietnam)

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.

Suggested Citation

  • Bui Thanh Danh, 2025. "Multi-Objective Optimization of Skd11 Steel Grinding Process using Entropy and RAM Methods," European Journal of Engineering and Technology Research, European Open Science, vol. 10(3), pages 1-5, May.
    • Handle: RePEc:epw:ejeng0:v:10:y:2025:i:3:id:63263
    DOI: 10.24018/ejeng.2025.10.3.3263
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