Parametric optimization of CNC milling of al 7075 using the TOPSIS multi-criteria decision-making method

This study presents a multi-response optimization of CNC milling parameters for Aluminium 7075 alloy using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). A Taguchi L27 orthogonal array was employed to investigate the effects of spindle speed, feed rate, and depth of cut under dry milling conditions. Cutting forces were measured using a KISTLER 9257B piezoelectric dynamometer with a National Instruments cDAQ-9174 data-acquisition system, while spindle power was monitored using a Hioki PW3198 power-quality analyser. Specific Cutting Energy (SCE) and resultant cutting force were considered non-beneficial responses and assigned equal weights in the primary TOPSIS analysis. The results indicate that increasing feed rate generally reduced SCE but increased resultant cutting force, while greater depth of cut increased cutting-force requirements. Higher spindle speed generally reduced resultant cutting force. The optimum combination was identified as 3700 rpm spindle speed, 450 mm/min feed rate, and 0.8 mm depth of cut, achieving a TOPSIS closeness coefficient of 0.858 for equal weighting. Sensitivity analysis confirmed this parameter combination as a recurrent optimum under different response weightings. The findings demonstrate the effectiveness of TOPSIS for balancing energy efficiency and cutting-force reduction in Aluminium 7075 milling.