Parametric study and multi-criteria optimization during turning of X210Cr12 steel using the desirability function and hybrid Taguchi-WASPAS method

Abstract

The present study examines the machining of a cold work tool steel (X210Cr12) using a triple chemical vapor deposition coated carbide tool (Al2O3/TiC/TiCN). The paper is focused on an experimental investigation as well as a modeling and optimization of the working cutting parameters in relationship with the studied material. For that, first, a set of experimental tests were built in order to evaluate the effect of cutting parameters (r, Vc, f, and ap) on the output parameters, namely surface roughness (Ra), cutting force (Fz), insert flank wear (Vb), and 3D roughness distribution. In a second step, a Taguchi L16 (4^3 2^1) design of experiment (DoE) was exploited with the aim to develop a modeling of output working parameters based on the response surface methodology. An optimization of the cutting conditions was performed using the desirability function (DF) approach and the hybrid Taguchi-weighted aggregate sum product assessment method. The desired objective is to obtain optimal cutting regime corresponding to the simultaneous minimization of parameters Ra and Fz, and maximization of material removal rate. The results found show that the factor f influences Ra with 42.55% and that parameter ap affects parameters Fz and Pc with 67.55 and 60.88%, respectively. For the DF and WASPAS methods, the optimal regimes selected is r = 1.6 mm, Vc = 366 m/min, ap = 0.17 mm, f = 0.16 mm/rev and r = 1.6 mm, Vc = 180 m/min, ap = 0.3 mm, and f = 0.08 mm/rev, respectively. The proposed work concerns all mechanical manufacturing companies, as it provides the necessary information on the optimal working conditions of the tool/material pair.

Experimental investigation on the performance of ceramics and CBN cutting materials during dry machining of cast iron: Modeling and optimization study using RSM, ANN, and GA

“…54 the desirability function (DF) method is widely used. [55][56][57] Compared to other multi-objective optimization techniques, it is powerful, simple and involves fewer computational steps. The following steps are used in (DFA) for the optimization of process parameters.…”

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

“…The material of study is high-alloy steel AISI D3, intended for cold work with a very high resistance to abrasive wear, medium toughness, dimensional stability, and high resistance to compression. This material has a wide application in the industrial field, such as in machining and forming tools such as punches, and rolling mills, as well as the manufacture of measuring instruments such as gauges, stamps, and gauges [25]. The chemical composition of AISI D3 steel is shown in Table 1.…”

“…On the other hand, AISI D3 high-alloy steel has been the subject of several experimental studies that focus on machinability, MQ lubrication, tool wear, modeling, and optimization of cutting conditions [13][14][15][16][17][18][19][20]. Also, the desirability function approach is among the multi-objective optimization methods extensively used in many industrial sectors because of the advantages it presents [21][22][23][24][25][26][27][28]. Several researchers have adopted the GRA method as a multi-objective optimization method for cutting conditions due to its effectiveness in making the right decision for selecting the optimal parameters [29][30][31][32][33][34][35].…”

Optimization of turning process parameters using a new hybrid evolutionary algorithm

“…Safi et al 15 applied the desirability function (DF) approach to minimize average surface roughness and the tangential cutting force and maximize of material removal rate during the turning of X210Cr12 steel. Recently, Nouioua et al 16 employed four recent swarms algorithms namely, the ant lion optimizer (ALO), salp swarm algorithm (SSA), GWO, and multiverse optimizer (MVO) for two objectives the tangential force and surface roughness.…”