Papers by Keyword: End Milling

Abstract: In this study, tool edge temperature was measured by a two-color pyrometer with an optional fiber and the novel method to evaluate the cooling effect of cutting fluid was proposed. After one cut, the tool edge passes over the fine hole at workpiece where inserted into an optical fiber so that the one peak signal can be obtained by each of two detectors with different spectral sensitivities in the pyrometer. The tool edge temperature can be calculated by taking the ratio of outputs from these two detectors. In previous research dealing with the cutting temperature in end milling obtained by a two-color pyrometer with an optional fiber, the average temperature calculated from some large peak values was used for an index as cutting temperature. However, this method was not suitable to estimate the tool edge temperature in wet milling. In the proposed method, the tool edge temperature was calculated only by the peak signals just after full length cut and used for an index as cutting temperature. The frequency distribution of tool edge temperature was made by the obtained temperature data. Comparing dry cutting to wet cutting, there was almost no difference in maximum temperature but obvious difference in the frequency distribution. The temperature range in wet cutting was wider than that in dry cutting.

Abstract: This paper discusses the cutting temperature and cutting force in end milling difficult-to-cut materials cooled with several types of mists and low-temperature air. The cutting tool was a throwaway end mill with a carbide tip coated with titanium aluminum nitride. The Ti-6Al-4V titanium alloy and AISI D2 hardened steel were used as workpieces. The tool flank temperature and cutting force were measured simultaneously during side milling. The temperature was measured using a two-color pyrometer with an optical fiber. Oil mist and water mist from a mist generator were supplied to the cutting point along with cold air at approximately -27 °C. Compared with dry cutting, the cooling effects of supplying an oil mist and/or cold air were less than for other supply conditions in titanium alloy cutting. However, when water mist was added, the tool flank temperature clearly decreased. The cutting force increased for cases that included water mist. The adhesion of the titanium alloy to the cutting edge of the worn tool was significantly suppressed by supplying water and oil mist with cold air. Tool flank wear also decreased under those lubrication conditions.

Abstract: Machining at high cutting speeds produces higher temperatures in the cutting zone. These temperatures affect the surface quality and flank wear progress. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness and flank wear is an important for it is economical and mechanical issues. This paper presents the optimization of machining parameters in end milling processes by using the simulated annealing algorithm (SAA) as one of the unconventional methods in optimization. The minimum arithmetic mean roughness (Ra) and minimum flank wear length were the objectives. The mathematical models have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response surface Methodology (RSM). This paper presents the optimum cutting parameters: cutting speed, feed rate and depth of cut to achieve the minimum values of surface roughness and minimum flank wear length. The results show that the cutting speed in the range of 200 m/min, feed rate of 0.05 mm/tooth and depth of cut of 0.1mm gave the minimum arithmetic mean roughness (Ra) for 164 and minimum flank wear for 0.0379 in the boundary design of the experiment after 8000 iteration.

Abstract: One of the significant characteristics in machining process is final quality of surface. The best measurement for this quality is the surface roughness. Therefore, estimating the surface roughness before the machining is a serious matter. The aim of this research is to estimate and simulate the average surface roughness (Ra) in high speed end milling. An experimental work was conducted to measure the surface roughness. A set of experimental runs based on box behnken design was conducted to machine carbon steel using coated carbide inserts. Moreover, the Adaptive Neuro-Fuzzy Inference System (ANFIS) has been used as one of the unconventional methods to develop a model that can predict the surface roughness. The adaptive-network-based fuzzy inference system (ANFIS) was found to be capable of high accuracy predictions for surface roughness within the range of the research boundaries.

Abstract: In order to pursue possibility to machine sintered Tungsten Carbide by milling, series of ball end milling experiments are carried out with use of ball end mills made of sintered PCD and sintered CBN to machine flat inclined surface of sintered Tungsten Carbide. The experimental results show that the sintered Tungsten Carbide can well be machined by end milling. The ball end milling is also applied to finish rounding of the edges of the gear teeth. The maximum surface roughness of the finished gear teeth obtained is 1.1μm.

Abstract: For a cutting process using a low-rigidity end mill, it is very important to be able to estimate the degree of machining error caused by the deflection of the tool. The purpose of this study is to establish a method of estimating, in real time, the machining error caused by the deflection at the cutting point of an end mill. To this end, in this research, a method for estimating the machining error caused by the deflection of the tool used for the ball-end milling of a hemispherical surface was verified by comparing the estimated and measured deflections of the tool. As a result, it was found that the machining errors in ball-end milling could be estimated from the normal force at the moment when the radial direction of the peripheral cutting edge is normal to the feed direction of the tool.

Abstract: Machining operations are performed by machine tools with a large amount of energy consumed for material removal. Understanding and characterizing the energy consumption is essential to explore the potential of energy-saving in energy-efficient machining. For this purpose, this paper proposes a method for modeling energy consumption of end milling operation which is based on cutting theory. The cutting power model is verified with experiments on a CNC milling machine. According to the calculated and experimental results, it is clear that the theoretical prediction can predict the mean cutting power successfully as validated by actual measurements.

Abstract: This paper presents the prediction method of cutting force and dimensional error of Ti6Al4V alloy thin-wall components in end-milling operations. Based on the FEM simulation software and force-model, machining deformation was predicted by two kinds of FEM models, and then compared with the measured data. Results obtained from the proposed models and the tests show that the coupling model of thermal-mechanical having better agreement with the experimental results. Besides, the test results also prove the new tool-path pattern proposed in this paper is useful to reduce the machining error.

Abstract: Surface roughness has a significant effect on the performance of machined components. In the present study, a total of 49 end milling experiments on AISI H13 steel are conducted. Based on the experimental results, the signal-to-noise (S/N) ratio is employed to study the effects of cutting parameters (axial depth of cut, cutting speed, feed per tooth and radial depth of cut) on surface roughness. An ANN predicting model for surface roughness versus cutting parameters is developed based on the experimental results. The testing results show that the proposed model can be used as a satisfactory prediction for surface roughness.

Abstract: The heat produced in metal cutting process is one of the most critical issue in machining of titanium alloys. High temperature in metal cutting degrades the tool life, surface integrity, size accuracy and machining efficiency dramatically. The temperature generated during end milling of titanium alloy, has been measured using Thermo camera. Surface roughness plays a vital role in evaluating and measuring the quality of the machined surface. During the experiments, cutting speed and feed rate have been changed to analyse the effect of temperature and surface roughness. It is observed that cutting speed has the greater effect on temperature and surface roughness during end milling of titanium alloy. The regression equations generated have better fit which can be used for optimization.