Optimization of machining parameters for kerf angle and roundness error in abrasive water jet drilling of CFRP composites with different fiber orientation angles

Abstract

In this study, carbon fiber-reinforced polymer (CFRP) composites with three different fiber orientation angles (M1: [0°/90°] s , M2: [+ 45°/− 45°] s , and M3: [0°/45°/90°/− 45°] s) were drilled (with and without pilot holes) on an abrasive water jet (AWJ) machine and the effect of the drilling parameters on the kerf angle (K) and roundness error (Re) of selected holes was investigated to determine quality characteristics. The first aim of the study was the single-objective optimization of drilling parameters for minimum K and Re individually. The second aim was the multi-objective optimization of drilling parameters for the simultaneous minimization of both K and Re. The Taguchi method was applied for single-objective optimization, while all steps of the Taguchi-based gray relational analysis were used for multi-objective optimization. Drilling experiments were performed using the L16 (4 4) orthogonal array. Four levels each for water pressure, stand-off distance, traverse feed rate, and hole diameter were selected as control factors. Analysis of experimental findings revealed that pilot drilling improved the kerf angle of the hole by 12.4% and the roundness error by 22.87%. Minimum kerf angle and roundness error were realized in the AWJ drilling of the M3 CFRP. The most effective parameter on kerf angle and roundness error in AWJ drilling of M1, M2, and M3 CFRP materials was water pressure (80.6%, 76.9%, and 73.8%, respectively), followed by stand-off distance (11.7%, 12.0%, and 13.5%),while other drilling parameters remained below 10%. The statistical evaluation and optimization results in this study can contribute to the evaluation of the AWJ machinability of CFRP composites.

Analysis of Surface Roughness and Flank Wear Using the Taguchi Method in Milling of NiTi Shape Memory Alloy with Uncoated Tools

“…According to this method, in order to perform statistical analysis, the Ra values were converted into the S/N ratio based on the "smaller is the better" approach ( Table 6). While the signal value represents the actual value given by the system that needs to be measured, the noise factor represents the rate of unwanted factors in the measured value [20]. In the experimental study, the Ra value was measured as 0.543 µm, and the average S/N ratio for the Ra value was obtained as 5.503 dB.…”

“…Since the softening occurring in the workpiece at high V c (50, m/min) is more than the thermal softening in the cutting tool, a decrease was observed in the Vb value of the cutting tool [3,27]. As seen in the graph in Figure 6b, the increase in the V c and f z at three different V c (20,35 and 50 m/min) and f z (0.03, 0.07 and 0.14 mm/tooth) depends on the increase in the cutting temperature between the cutting tool and the workpiece. It is thought that the chemical reaction occurring between the carbide cutting tool and the workpiece with the influence of increasing temperature affects the wear on the cutting tool and increases Vb formation [3,26,27].…”

“…To specify the quality characteristic of validation experiments, the confidence interval (CI) was calculated. The CI predictive optimum quality characteristics for Ra _opt and Vb _opt were calculated using Equation (3) [20].…”

“…In Equation 4, "T exp " is the total number of experiments, and "dof" is the total degree of freedom of the factors used for estimation [20].…”

Experimental investigation on machining of hardstone quartz with modified AJM using hot silicon carbide abrasives

“…Under such circumstances, the effective utilization of experimental, modeling, and optimization methodology makes possible a greater improvement in decision-making with new technological solution that can simultaneously satisfy and control the several distinctive as well as contradictory objectives (multi-objective) in order to make the HAJM process as an excellent choice for machining of advanced engineering ceramic and quartz materials. Several statistical and computational approaches such as MRA [1][2][3], RSM [4][5][6][7][8][9], ANN [10][11][12][13] have been applied for predictive modeling and Taguchi method [14][15][16][17][18], GRA [19][20][21][22][23][24][25], desirability function approach of RSM [26][27][28][29][30][31][32], PCA [33,34], TOPSIS [35], GA [11,12,36,37], PSO [38,39] have been employed for parametric as well as process optimization in abrasive jet machining with the help of carrier gas or liquid medium. Extensive studies have been reported by employing various experimental designs, modeling techniques, and optimization approaches in order to assess or investigate th...…”