Modeling and multi-response optimization of cutting parameters in turning of AISI 316L using RSM and desirability function approach

benkhelifa, oussama; Cherfia, Abdelhakim; Nouioua, Mourad

doi:10.1007/s00170-022-10044-2

Cited by 12 publications

(1 citation statement)

References 32 publications

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“…The method is widely used in solving multi-objective optimization problems because of its simplicity and effectiveness in putting in the hands of the users the best solutions for choosing the cutting parameters that ensure the global objective aimed at. DF with the value closest to 1 indicates the optimal combination of cutting parameters [46]. It is given by the following equations:…”

Section: Desirability Functionmentioning

confidence: 99%

Statistical analysis, modeling and multi-objective optimization of parameters intermittent turning process of AISI D3

Khelfaoui

Yallese

Ouelaa

et al. 2023

JMES

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Intermittent machining is characterized by its complex and irregular context. This intermittency causes machining to occur under difficult conditions that greatly influence the technological performance parameters. The aim of the present work is to evaluate the effects of input parameters, cutting speed, Vc, depth of cut, ap, tool nose radius, r and feed rate, f, on surface roughness, Ra, tangential cutting force, Fz, motor power consumption, Pm, cutting power, Pc and material removal rate (MRR), during intermittent turning (IT) of AISI D3 tool steel. Machining was performed with a triple CVD coated carbide tool (AI2O3/TiC/TiCN) by adopting a Taguchi L9 (3^4) experimental design. The ANOVA and RSM methods were used to analyze the effects of cutting factors on the outputs parameters resulting in statistical prediction models. In addition, a multi-objective optimization of the cutting conditions exploiting the desirability function (DF) was done according to four cases of relative importance corresponding to different industrial contexts. Furthermore, the grey relational analysis (GRA) method was applied and compared with the DF method. The results show that the optimal regime found by the DF method, (r =1.6mm, Vc= 240 m/min, f = 0.084 mm/rev and ap = 0.64 mm), favors Ra and MRR. On the other hand, for the GRA method, the combination of (r = 0.4 mm, Vc = 240 m/min f = 0.08 mm/rev and ap = 0.3 mm) favors the minimization of Fz, Pm and Pc. This work presents an originality because the results found are very useful in the field of optimization for a better control of the process IT.

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Section: Desirability Functionmentioning

confidence: 99%