Süleyman Neşeli

Prediction of surface roughness using artificial neural network in lathe

In this study, the effect of tool geometry on surface roughness has been investigated in universal lathe. Machining process has been carried out on AISI 1040 steel in dry cutting condition using various insert geometry at depth of cut off 0.5 mm. At the end of the cutting operation, surface roughness has been measured using MAHR M1 perthometer. After experimental study, to predict the surface roughness, an ANN has been modelled using the data obtained. Modelling of ANN; tool nose radius (r), approach angle (K), rake angle (Y), tool overhang (L) have been used. In this study, surface roughness (Ra) is output data. The ANN has been designed on PC by using Matlab 6.5 software. Comparison of the experimental data and ANN results by means of statistically t test show that there is no significant difference and ANN has been used confidently.

Three-dimensional finite element modeling of effect on the cutting forces of rake angle and approach angle in milling

In this study, milling operations were carried out using AISI 1040 specimens steel in dry cutting conditions. The cutting tools used in the experiment include P20 tool steel and they also have three different approach angles (45°, 60°, 75°) and rake angles (0°, −6°, −12°). In milling experiments, cutting parameters with a depth of cut of 1.5 mm, cutting speed of 193 m/min, and feed rate of 313 mm/min were selected. A comparison was presented between the force values which were obtained by measured value and predicted with numerical simulations, and then a good agreement was found between measured and predicted force values. As result of, it was observed that the rake and approach angles were effective in milling operations.

Optimization of Process Parameters with Minimum Thrust Force and Torque in Drilling Operation Using Taguchi Method

This research outlines the Taguchi optimization methodology, which is applied to optimize cutting parameters in drilling of AISI 1040 steel. The drilling parameters evaluated are cutting speed, feed rate, and helix angle. Series of experiments are conducted to relate the cutting parameters on the thrust force and torque. L27(313) orthogonal array, signal-to-noise ratio is employed to analyze the influence of these parameters on thrust force and torque during drilling. Analysis of variance (ANOVA) is used to study the effect of process parameters on machining process. The study shows that the Taguchi method is suitable to solve the stated problem with the minimum number of trials. The main objective is to find the important factors and combination of factors that influence the machining process to achieve low thrust force and torque. The analysis of the Taguchi method indicates that the feed rate is the most significant factor affecting the thrust force, while the cutting speed contributes the most to the torque.