Nihat Tosun

Investigation of the wear behaviour of a glass-fibre-reinforced composite and plain polyester resin

In industrial applications, the increase in the use of composite materials means that it is necessary to know their behaviour under working conditions. Wear is an important parameter and its experimental behaviour must be known. In this study, the wear behaviour of a glass-fibre-reinforced composite and plain polyester resin are experimentally investigated for speeds of 500 and 710 rpm and at two different loads of 500 and 1000 g by the use of a block-on-disk wear tester. Wear in the experiments was determined as weight loss. The weight losses were measured after sliding distances of 235.5, 471, 706.5, 942, 1177.5, 1413, 1648.5 and 1884 mm. In addition, photographs of specimens were taken under the SEM and the wear behaviour in these photographs was investigated.

A study of tool life in hot machining using artificial neural networks and regression analysis method

Abstract In this study, the high manganese steel specimens heated with liquid petroleum gas flame were machined on a lathe under different cutting conditions of feed rates, depth of cuts, cutting speeds and surface temperatures. A mathematical model for tool life was obtained from the experimental data using a regression analysis method. In addition, the tool life was estimated using artificial neural network (ANN) with backpropagation (BP) algorithm. Then, this program was trained and tested. Finally, the experimental data are compared with both the regression analysis results and the estimations of ANN.

The Effect of Cutting Parameters on Workpiece Surface Roughness in Wire EDM

In this study, the variation of workpiece surface roughness with varying pulse duration, open circuit voltage, wire speed and dielectric fluid pressure was experimentally investigated in Wire Electrical Discharge Machining (WEDM). Brass wire with 0.25 mm diameter and SAE 4140 steel with 10 mm thickness were used as tool and workpiece materials in the experiments, respectively. It is found experimentally that the increasing pulse duration, open circuit voltage and wire speed, increase the surface roughness whereas the increasing dielectric fluid pressure decreases the surface roughness. The variation of workpiece surface roughness with machining parameters is modelled by using a power function. The level of importance of the machining parameters on the workpiece surface roughness is determined by using analysis of variance (ANOVA).

Effect of MQL on Surface Roughness in Milling of AA7075-T6

In this study, the effect of cutting parameters and cooling technique on the workpiece surface roughness in milling of 7075-T6 aluminum alloy was experimentally investigated. Experiments were conducted under different spindle speed, feed rate, cooling technique (conventional and minimum quantity lubrication), and cutting tool material. The effect of volumetric concentration of solution for minimum quantity lubrication (MQL) was also investigated. The cutting fluid is a mixture of boron oil and water. The cutting fluid in milling with MQL was delivered to the interface workpiece and cutting tool as atomize. The experimental results for surface roughness were statistically analyzed by using analysis of variance (ANOVA).

The Effect of the Cutting Parameters on Performance of WEDM

In this study, variations of cutting performance with pulse time, open circuit voltage, wire speed and dielectric fluid pressure were experimentally investigated in Wire Electrical Discharge Machining (WEDM) process. Brass wire with 0.25 mm diameter and AISI 4140 steel with 10 mm thickness were used as tool and work materials in the experiments. The cutting performance outputs considered in this study were surface roughness and cutting speed. It is found experimentally that increasing pulse time, open circuit voltage, wire speed and dielectric fluid pressure increase the surface roughness and cutting speed. The variation of cutting speed and surface roughness with cutting parameters is modeled by using a regression analysis method. Then, for WEDM with multi-cutting performance outputs, an optimization work is performed using this mathematical models. In addition, the importance of the cutting parameters on the cutting performance outputs is determined by using the variance analysis (ANOVA).

Analysis of Process Parameters for Porosity in Porous NiTi Implants

This article presents optimization of process parameters for the porosity in NiTi alloy produced as implant material by self-propagating high-temperature synthesis (SHS) method. The experiments were conducted under the different process parameters, namely, compaction pressure, preheating temperature, and heating rate. A plan of experiments based on the Taguchi method was designed. The level of importance of the process parameters is determined by using analysis of variance (ANOVA). The optimum process parameter combination was obtained by using the analysis of signal-to-noise (S/N) ratio. Through statistical analysis of response variables and S/N ratios, the determined significant factors were the heating rate and pressure. By using regression analysis method, the variation of the porosity in the implant with production parameters is mathematically modeled.

Abrasive Waterjet Cutting of Aluminum Alloys: Workpiece Surface Roughness

Abrasive waterjet machining is one of the non-traditional methods of the recent years which found itself a wide area of application in the industry for machining of different materials. In this paper, the surface roughness of 6061-T6 and 7075-T6 aluminum alloys are being cut with abrasive waterjet is examined experimentally. The experiments were conducted with different waterjet pressures and traverse speeds. It has been found that the surface roughness obtained by cutting material with high mechanical properties is better than that of obtained by cutting material with inferior mechanical properties.