English Abstract
Abstract:
End-milling operation of steel grade material is a challenging task as it is hard-to-cut
material. Proper selection of cutting tools, cutting conditions, and cutting process parameters
is important to improve productivity, surface quality, and tool life. Therefore, the present study
investigated the end-milling operation of AISI 1522H steel grade under minimum-quantity lubrication
(MQL) conditions using a novel blend of vegetable oils, namely canola and olive oil. Cutting process
parameters considered were spindle speed (s), feed rate (f ), depth of cut (d), width of cut (w), and
cutting conditions (c), while responses were average surface roughness (Ra), cutting forces (Fc),
tool wear (TW), and material removal rate (MRR). Experimental runs were designed based on the
definitive screening design (DSD) method. Analysis of variance (ANOVA) results show that feed
rate significantly affects all considered responses. Nonlinear prediction models were developed for
each response variable, and their validity was also verified. Finally, multi-response optimization
was performed using the combinative distance-based assessment (CODAS) method coupled with
criteria importance through inter-criteria correlation (CRITIC). The optimized parameters found
were: s = 1200 rpm, f = 320 mm/min, d = 0.6 mm, w = 8 mm, and c = 100 mL/h. Further, it was
compared with other existing multi-response optimization methods and induced good results.
