Abstract

SKD-61 steel finds extensive application in various sectors, including the marine industry where materials must withstand harsh aquatic conditions. In this study, we employ the Grey-Taguchi approach to optimize surface roughness (Ra), cutting force (Fc), and material removal rate (MRR) when hard-milling SKD-61 steel in pure minimum quantity lubrication (MQL) and nanofluid MQL environments, aligning with the demands of marine engineering. The orthogonal array method generates a set of experiments based on four input parameters: cutting speed, depth of cut, feed per tooth, and cutting condition, which are essential factors in marine component manufacturing. Our approach combines Grey relational analysis (GRA) with the Taguchi method to enhance multi-objective outcomes in machining. The results of this marine-focused study reveal that the lowest surface roughness, cutting force, and highest material removal rates are attained when the cutting conditions align with the principles of nanofluid MQL at a cutting velocity of 80 m/min, a depth of cut of 0.2 mm, and a feed per tooth of 0.01 mm/tooth. Keywords: hard milling, nanofluid MQL, optimization machining parameters; Grey relational analysis; Taguchi

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