<![CDATA[This research focuses on optimizing CNC turning parameters to achieve the best surface quality on Aluminum 7075 material. Surface quality, measured by surface roughness (Ra), is the primary target, while material removal rate (MRR) is considered as a supporting factor to maintain productivity. The Taguchi L9 method was used to design experiments by varying three key parameters: cutting speed (Vc), feed rate (f), and depth of cut (ap). Each parameter combination was tested, and the responses in the form of Ra and MRR values were recorded. To address the conflict between surface quality and productivity, multi-response analysis was conducted using the Grey Relational Analysis (GRA) technique. This method combines both responses into a single performance indicator, the grey relational grade (GRG), enabling comprehensive determination of optimal parameters. The analysis results show that the optimal combination is achieved at high cutting speed, low feed rate, and medium depth of cut. This setting significantly reduced surface roughness by 31.2% compared to the initial parameters while maintaining MRR at an acceptable level. Analysis of variance (ANOVA) confirmed that cutting speed is the most dominant factor (67.3% contribution) affecting the surface quality of the turning results. This research provides an effective and systematic parameter recommendation for improving final product quality in precision manufacturing processes.]]>
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