Randomized trial optimizes machining parameters for improved surface quality and efficiency in aluminum alloy.
The extensive use of aluminum alloys across demanding fields, such as aerospace and automotive engineering, drives a strong emphasis within production industries to enhance manufacturing efficiency and achieve cost savings. In this paper, milling of Al7075 has been conducted using response surface methodology (RSM). Three process parameters, tool speed ([Formula: see text], depth of cut ([Formula: see text], and feed rate ([Formula: see text], have been selected at three levels. The performance measures, the material removal rate (MRR) and surface roughness (SR), are selected, studied, and observed during the experimentation process. The results are modeled and statistically analyzed using an RSM-based central composite rotatable design (CCRD). ANOVA results show that both models have been found significant. The multi-objective optimization (MOO) uses an RSM-based desirability function. A set of 10-best results (combinations of process parameters), obtained to maximize MRR and minimize SR, yields the desirability value [Formula: see text] 0.611, maximum MRR [Formula: see text] 27.144 mm 3 /min, and minimum SR [Formula: see text] 2.925 [Formula: see text]m. The corresponding optimal process parameters have been found to be [Formula: see text] rpm, [Formula: see text] mm, and [Formula: see text] mm/min. The confirmatory results show that the values of MRR and SR have been found as 29.365 mm 3 /min and 2.884 [Formula: see text]m, respectively. The percentage changes, determined as 8.18 and 1.40, have been found significant, corresponding to the predicted values.
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Hari Om (2026) studied this question.
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