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Journal : STEAM Engineering : Journal of Science, Technology, Education And Mechanical Engineering

OPTIMASI PARAMETER PEMOTONGAN CNC WET MILLING TERHADAP KEKASARAN PERMUKAAN STAINLESS STEEL AISI 304 Deni Mulyana; Ilham Azmy; Alvaro Gabrian; Rudy Yuni Widiatmoko; Petrus Londa
Steam Engineering Vol. 4 No. 1 (2022): STEAM Engineering, Vol. 4, No. 1, September 2022
Publisher : Program Studi Pendidikan Teknik Mesin, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (594.069 KB) | DOI: 10.37304/jptm.v4i1.5269

Abstract

Optimization of CNC wet milling cutting parameters for stainless steel AISI 304 was successfully attempted by using Taguchi method (S/N ratio and ANOVA). L9 orthogonal array is utilized for designing the experiments with 3 levels of spindle speeds and feed rates with an increment depth of cut. The effect of cutting parameters on surface roughness was examined. According to S/N ratio’s response table, the result obtained for spindle speed fervently indicates that spindle speed is the most pivotal factor for impacting the surface roughness than feed rate for stainless steel AISI 304. ANOVA results depicted that the contribution percentage of spindle speed for surface roughness is higher than feed. Optimum values of cutting parameters were endowed at a spindle speed of 3184 rpm and a feed rate of 1528,4 mm/min. The experimental values at optimum cutting condition were compared with predicted values and it reveals a significant congruity with the experimental results with a low error percentage. Therefore, this experiment aims to develop the productivity and quality of CNC milling operations for stainless steel AISI 304. In addition, number of studies for cutting parameter optimization stainless steel AISI 304 was not barely done yet. Hereafter, more investigations still needed to optimize the cutting parameters of this stainless steel AISI 304 for various machining operations specifically on CNC milling process.