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The purpose of this study is to investigate the effect of new green hexagonal boron nitride (hBN) nanofluid on AISI 316L stainless friction coefficient, wear resistance and wear using a ball on disc tester.

Nanofluids were prepared by adding hBN nanoparticles with two-step method to the vegetable-based oil at 0.50 vol%. Before the experiments, hBN nanofluid viscosity, pH and thermal conductivity specifications were determined. Friction tests of AISI 316L stainless steel were performed under 2 N, 5 N and 8 N loads at 400 rpm using a ball-on-disc test device under dry, oil and hBN conditions. Coefficient of friction, wear profile, surface integrity and wear mechanisms were chosen as performance criteria.

The friction coefficient values obtained under the oil and hBN test conditions with the 8 N load were, respectively, 72.46% and 77.64% lower than those obtained under dry test conditions. hBN nanofluid performed better on surface topography, and especially wear, compared to the dry and oil test conditions.

The aim of this study was to determine the best tribological performance of the hBN nanofluid on AISI 316L stainless steel used in orthopedic applications.

The paper is a study investigating the effect of hBN nanoparticle additive in vegetable-based oil on friction and wear performance of AISI 316L stainless steel. It is an original paper and is not published elsewhere.

The purpose of this study is to optimize processing parameters to get the smallest average surface roughness (Ra) and delamination damage (F_d) values during drilling via abrasive water jet (AWJ) of the glass fiber-reinforced polymer composite material produced at [0°/90°]_s fiber orientation angles.

Drilling experiments were done via AWJ with three-axis computer numerical control (CNC) control system. Machine processing parameters such as water pressure of 3,600, 4,300, 4,800 and 5,300 bar; stand-off distance of 1, 2, 3 and 4 mm; traverse rate of 750, 1,500, 2,000 and 3,000 mm/min; and hole diameters of 8, 10, 12 and 14 mm have been selected. The effects of processing parameters in drilling experiments were investigated in conformity with the Taguchi L₁₆ orthogonal array and the data obtained were analyzed using Minitab 17 software. The signal/noise (S/N) ratio was taken as a basis for evaluating the test results. Optimum processing conditions were determined by calculating the S/N ratio for both Ra and F_d in conformity with the “smaller is better” approximation. The effects of processing parameters on Ra and F_d were statistically investigated using analysis of variance, S/N ratio and Taguchi-based gray relational analysis. Ra and F_d were predicted by evaluating with the ANN model and were predicted with the least amount of error.

It has been determined that the most effective parameter for Ra and F_d is the water pressure and then the stand-off distance.

The novel approach is to reduce cost and the time spent by using Taguchi optimization as a result of AWJ drilling the material in this fiber orientation [0°/90°]_s.