Abstract
Stainless steel has various scientific, engineering, medical, and industrial applications. It undergoes extensive machining operations to make products for the aforementioned applications. Stainless steel is a difficult-to-machine material and requires novel ways and optimum parameter combinations for better machinability. In view of this, the present work investigates the machinability of SS304 using coated and uncoated carbide tools under dry environment. The machinability indicators studied in the present work are material removal rate (MRR), chip reduction coefficient (CRC), maximum surface roughness (Rt) and tool flank wear. Fuzzy logic integrated with multi objective optimization by ratio analysis (MOORA) has been used for the prediction of performance index (PI). The PI solved by fuzzy logic and MOORA is termed as MOORA-Fuzzy performance index (MFPI). This MFPI has been solved by regression analysis to predict the optimal parametric setting for multi-criteria decision making (MCDM) approach. The parametric combination i.e. cutting speed: 170 m/min; feed rate: 0.2 mm/rev; and depth of cut: 1.5mm has obtained as the optimal setting. The ANOVA results and confirmation experiments verify the superiority of the proposed model. The experimental results at the predicted setting represent excellent results regeneration.