高速铣削过程中表面粗糙度变化规律的试验研究

在高速铣削试验的基础上 ,研究分析切削速度与进给量对加工表面粗糙度的影响。试验数据表明 ,切削速度的提高有利于改善加工表面粗糙度 ,当切削速度超过某一范围后 ,随切削速度的进一步提高 ,加工表面粗糙度的降低并不明显 ,有时还会使表面粗糙度增加。根据试验结果 ,对具体工件材料与刀具材料匹配选择合理的切削速度与进给量范围 ,可以获得最小加工表面粗糙度值     

Machining performance of a grooved tool in dry machining Ti-6Al-4 V

In this paper, dry machining experiment of Ti-6Al-4 V was carried out to investigate the machining performance of a grooved tool in terms of its wear mechanisms and the effects of cutting parameters (cutting speed, feed rate, and cutting depth) on tool life and surface roughness of the machined workpiece. The results showed that chip-groove configuration substantially improved the machining performance of cutting tool. The main wear mechanisms of the grooved tool were adhesive wear, stripping wear, crater wear, and dissolution-diffusion wear. The resistance to chipping was enhanced due to the decrease of contact pressure of tool-chip interface. And the resistance to plastic deformation of tool nose was weakened at the cutting speed of more than 60 m/min. The appropriate cutting speed and feed rate were less than 70 m/min and 0.10 mm/r, respectively. With cutting speed increasing, the surface roughness of machined workpiece decreased. A high feed rate helped the formation of higher surface roughness except 0.21 mm/r. When cutting depth increased, tool nose curvature and phase transformation of workpiece material had great impact on surface roughness.     

Multi-response optimization of machining parameters in hot turning using grey analysis

This paper envisages the multi-response optimization of machining parameters in hot turning of stainless steel (type 316) based on Taguchi technique. The workpiece heated with liquid petroleum gas flame burned with oxygen was machined under different parameters, i.e., cutting speed, feed rate, depth of cut, and workpiece temperature on a conventional lathe. The effect of cutting speed, feed rate, depth of cut, and workpiece temperature on surface roughness, tool life, and metal removal rate have been optimized by conducting multi-response analysis. From the grey analysis, a grey relational grade is obtained and based on this value an optimum level of cutting parameters has been identified. Furthermore, using analysis of variance method, significant contributions of process parameters have been determined. Experimental results reveal that feed rate and cutting speed are the dominant variables on multiple performance analysis and can be further improved by the hot turning process.     

Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel

In this study, the effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and resultant forces in the finish hard turning of AISI H13 steel were experimentally investigated. Cubic boron nitrite inserts with two distinct edge preparations and through-hardened AISI H13 steel bars were used. Four-factor (hardness, edge geometry, feed rate and cutting speed) two-level fractional experiments were conducted and statistical analysis of variance was performed. During hard turning experiments, three components of tool forces and roughness of the machined surface were measured. This study shows that the effects of workpiece hardness, cutting edge geometry, feed rate and cutting speed on surface roughness are statistically significant. The effects of two-factor interactions of the edge geometry and the workpiece hardness, the edge geometry and the feed rate, and the cutting speed and feed rate also appeared to be important. Especially honed edge geometry and lower workpiece surface hardness resulted in better surface roughness. Cutting-edge geometry, workpiece hardness and cutting speed are found to be affecting force components. The lower workpiece surface hardness and honed edge geometry resulted in lower tangential and radial forces.     

高速切削中工件热变形误差形成机理研究

在三维车削模型的基础上,使用有限元软件Deform-3D对高速切削中车削速度、进给速度和背吃刀量进行了正交车削试验。根据试验结果提出了三维车削模型的工件热变形误差形成机理,在此基础上从刀具和加工工艺的角度提出了减少工件热变形误差的方法。     

Investigation of the direction of chip motion in diamond turning

Management of the chips generated in diamond turning is often critical since contact between chips and the workpiece can result in superficial damage to the finished surface. Controlling chip motion is not a trivial process as the proper positioning of an oil or an air stream requires an understanding of the dynamics of a diamond turned chip and the machining parameters that affect it. Previous work [1] introduced the chip curvature parameter, χ, which is useful in predicting chip radius of curvature over a wide range of cutting speeds, depths of cut, tool geometries and workpiece material properties. To control chip motion, however, an understanding of the direction chips leave the tool/workpiece interface must also be obtained. Cutting experiments were performed investigating the influence of cutting speed, depth of cut, feed rate, tool path angle, tool geometry and tool orientation on the directional characteristics of the motion of diamond turned chips. Flow angle measurements obtained during cutting were found to remain within ± 10° of predictions from a simple geometrical model originally proposed for conventional machining.     

Effect of work material hardness and cutting parameters on performance of coated carbide tool when turning hardened steel: An optimization approach

In present work performance of coated carbide tool was investigated considering the effect of work material hardness and cutting parameters during turning of hardened AISI 4340 steel at different levels of hardness. The correlations between the cutting parameters and performance measures like cutting forces, surface roughness and tool life, were established by multiple linear regression models. The correlation coefficients found close to 0.9, showed that the developed models are reliable and could be used effectively for predicting the responses within the domain of the cutting parameters. Highly significant parameters were determined by performing an Analysis of Variance (ANOVA). Experimental observations show that higher cutting forces are required for machining harder work material. These cutting forces get affected mostly by depth of cut followed by feed. Cutting speed, feed and depth of cut having an interaction effect on surface roughness. Cutting speed followed by depth of cut become the most influencing factors on tool life; especially in case of harder workpiece. Optimum cutting conditions are determined using response surface methodology (RSM) and the desirability function approach. It was found that, the use of lower feed value, lower depth of cut and by limiting the cutting speed to 235 and 144 m/min; while turning 35 and 45 HRC work material, respectively, ensures minimum cutting forces, surface roughness and better tool life.     

The effect of cutting parameters and cutting tools on machining performance of carbon graphite material

Abstract

The present study focuses on the effects of cutting speed, feed rate and cutting tool material on the machining performance of carbon graphite material. Polycrystalline Diamond (PCD) cutting tools are used in machining experiments and its performance is compared with the tungsten carbide (WC) and Cubic Boron Nitride (CBN) tools. Machining performance criteria such as flank and nose wear and resulting surface topography and roughness of machined parts were studied. This study illustrates that feed rate and cutting tool material play a dominant role in the progressive wear of the cutting tool. The highest feed rate and cutting speed profoundly reduce the tool wear progression. The surface roughness and topography of specimens are remarkably influenced from the tool wear. Major differences are found in the wear mechanisms of PCD and WC and CBN cutting tools.     

Effects of the cutting feed, depth of cut, and workpiece (bore) diameter on the tool wear rate

Most published studies on metal cutting regard the cutting speed as having the greatest influence on tool wear and, thus, tool life, while other parameters and characteristics of the cutting process have not attracted as much attention in this respect. This is because of the existence of a number of contradicting results on the influence of the cutting feed, depth of cut, and workpiece (bore) diameter. The present paper discusses the origin of the aforementioned contradicting results. It argues that, when the optimal cutting temperature is considered, the influence of the aforementioned parameters on tool wear becomes clear and straightforward. The obtained results reveal the true influence of the cutting feed, diameter of the workpiece, and diameter of the hole being bored on the tool wear rate. It was also found that the depth of cut does not have a significant influence on the tool wear rate. The obtained results provide methodological help in the experimental assessment and proper reporting of the tool wear rates studied under different cutting conditions.     

Nd-Fe-B烧结永磁材料的车削加工研究

对Nd-Fe-B烧结永磁材料的车削加工进行了试验研究。用线性断裂力学的方法建立了硬脆材料车削加工时的材料去除模型。探讨了车削过程中背吃刀量、进给量和车削速度对车削力及加工表面质量的影响，采用多元回归分析方法得出了主车削力的经验公式，并给出了用于检验回归结果与试验结果符合程度的误差评判参数。分析了Nd-Fe-B烧结永磁材料车削过程中刀具的磨损状况，以及刀具几何参数对加工质量的影响。     

Deformation behaviour of sintered silicon–copper steel preforms of various aspect ratios during cold upsetting

This paper presents the optimization of the face milling process of 7075 aluminum alloy by using the gray relational analysis for both cooling techniques of conventional cooling and minimum quantity lubrication (MQL), considering the performance characteristics such as surface roughness and material removal rate. Experiments were performed under different cutting conditions, such as spindle speed, feed rate, cooling technique, and cutting tool material. The cutting fluid in MQL machining was supplied to the interface of work piece and cutting tool as pulverize. An orthogonal array was used for the experimental design. Optimum machining parameters were determined by the gray relational grade obtained from the gray relational analysis.     

FUZZY CLUSTERING MODELLING FOR SURFACE FINISH PREDICTION IN FINE TURNING PROCESS

In this paper, fuzzy subtractive clustering based system identification and Sugeno type fuzzy inference system are used to model the surface finish of the machined surfaces in fine turning process to develop a better understanding of the effect of process parameters on surface quality. Such an understanding can provide insight into the problems of controlling the quality of the machined surface when the process parameters are adjusted to obtain certain characteristics. Surface finish data were generated for aluminum alloy 390 (73 BHN), ductile cast iron (186 BHN), and inconel 718 (BHN 335) for a wide range of machining conditions defined by cutting speed, cutting feed rate and cutting tool nose radius. These data were used to develop a surface finish prediction fuzzy clustering model as a function of hardness of the machined material, cutting speed, cutting feed rate, and cutting tool nose radius. Surface finish of the machined part is the output of the process. The model building process is carried out by using fuzzy subtracting clustering based system identification in both input and output space. Minimum error is obtained through numerous searches of clustering parameters. The fuzzy logic model is capable of predicting the surface finish for a given set of inputs (workpiece hardness, cutting speed, cutting feed rate and nose radius of the cutting tool). As such, the machinist may predict the quality of the surface for a given set of working parameters and may also set the process parameters to achieve a certain surface finish. The model is verified experimentally by further experimentation using different sets of inputs. This study deals with the experimental results obtained during fine turning operation. The findings indicate that while the effects of cutting feed and tool nose radius on surface finish were generally consistent for all materials, the effect of cutting speed was not. The surface finish improved for aluminum alloy and ductile cast iron but it deteriorated with speed for inconel.     

FUZZY CLUSTERING MODELLING FOR SURFACE FINISH PREDICTION IN FINE TURNING PROCESS

ABSTRACT

In this paper, fuzzy subtractive clustering based system identification and Sugeno type fuzzy inference system are used to model the surface finish of the machined surfaces in fine turning process to develop a better understanding of the effect of process parameters on surface quality. Such an understanding can provide insight into the problems of controlling the quality of the machined surface when the process parameters are adjusted to obtain certain characteristics. Surface finish data were generated for aluminum alloy 390 (73 BHN), ductile cast iron (186 BHN), and inconel 718 (BHN 335) for a wide range of machining conditions defined by cutting speed, cutting feed rate and cutting tool nose radius. These data were used to develop a surface finish prediction fuzzy clustering model as a function of hardness of the machined material, cutting speed, cutting feed rate, and cutting tool nose radius. Surface finish of the machined part is the output of the process. The model building process is carried out by using fuzzy subtracting clustering based system identification in both input and output space. Minimum error is obtained through numerous searches of clustering parameters. The fuzzy logic model is capable of predicting the surface finish for a given set of inputs (workpiece hardness, cutting speed, cutting feed rate and nose radius of the cutting tool). As such, the machinist may predict the quality of the surface for a given set of working parameters and may also set the process parameters to achieve a certain surface finish. The model is verified experimentally by further experimentation using different sets of inputs. This study deals with the experimental results obtained during fine turning operation. The findings indicate that while the effects of cutting feed and tool nose radius on surface finish were generally consistent for all materials, the effect of cutting speed was not. The surface finish improved for aluminum alloy and ductile cast iron but it deteriorated with speed for inconel.     

The optimal cutting-parameter selection of heavy cutting process in side milling for SUS304 stainless steel

This paper presents an optimal cutting-parameter design of heavy cutting in side milling for SUS304 stainless steel. The orthogonal array with grey-fuzzy logics isapplied to optimize the side milling process with multiple performance characteristics. A grey-fuzzy reasoning grade obtained from the grey-fuzzylogics analysis is used as a performance index to determine the optimal cutting parameters. The selected cutting parameters are spindle speed, feed per tooth,axial depth of cut and radial depth of cut, while the considered performance characteristics are tool life and metal removal rate. The results ofconfirmation experiments reveal that grey-fuzzy logics can effectively acquire an optimal combination of the cutting parameters. Hence, performance in theside milling process for heavy cutting can be significantly improved through this approach.     

Surface roughness and cutting forces modeling for optimization of machining condition in finish hard turning of AISI 52100 steel

An experimental investigation was conducted to analyze the effect of cutting parameters (cutting speed, feed rate and depth of cut) and workpiece hardness on surface roughness and cutting force components. The finish hard turning of AISI 52100 steel with coated Al₂O₃ + TiC mixed ceramic cutting tools was studied. The planning of experiment were based on Taguchi’s L₂₇ orthogonal array. The response table and analysis of variance (ANOVA) have allowed to check the validity of linear regression model and to determine the significant parameters affecting the surface roughness and cutting forces. The statistical analysis reveals that the feed rate, workpiece hardness and cutting speed have significant effects in reducing the surface roughness; whereas the depth of cut, workpiece hardness and feed rate are observed to have a statistically significant impact on the cutting force components than the cutting speed. Consequently, empirical models were developed to correlate the cutting parameters and workpiece hardness with surface roughness and cutting forces. The optimum machining conditions to produce the lowest surface roughness with minimal cutting force components under these experimental conditions were searched using desirability function approach for multiple response factors optimization. Finally, confirmation experiments were performed to verify the pertinence of the developed empirical models.     

Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool

Hard turning with multilayer coated carbide tool has several benefits over grinding process such as, reduction of processing costs, increased productivities and improved material properties. The objective was to establish a correlation between cutting parameters such as cutting speed, feed rate and depth of cut with machining force, power, specific cutting force, tool wear and surface roughness on work piece. In the present study, performance of multilayer hard coatings (TiC/TiCN/Al₂O₃) on cemented carbide substrate using chemical vapor deposition (CVD) for machining of hardened AISI 4340 steel was evaluated. An attempt has been made to analyze the effects of process parameters on machinability aspects using Taguchi technique. Response surface plots are generated for the study of interaction effects of cutting conditions on machinability factors. The correlations were established by multiple linear regression models. The linear regression models were validated using confirmation tests. The analysis of the result revealed that, the optimal combination of low feed rate and low depth of cut with high cutting speed is beneficial for reducing machining force. Higher values of feed rates are necessary to minimize the specific cutting force. The machining power and cutting tool wear increases almost linearly with increase in cutting speed and feed rate. The combination of low feed rate and high cutting speed is necessary for minimizing the surface roughness. Abrasion was the principle wear mechanism observed at all the cutting conditions.     

Influence of the process variables on the temperature distribution in orthogonal machining using the finite element method

The temperature distributions in the workpiece, tool and chip during orthogonal machining are obtained numerically using the Galerkin approach of the finite element method for various cutting conditions. The effect of a number of process variables such as speed, feed, coolant, rake angle, tool flank wear and tool material on the temperatures has been investigated.     

Fabricating micro-structured surface by using single-crystalline diamond endmill

A ball endmill made of single-crystalline diamond was used for cutting micro-structures on two kinds of mold materials, oxygen-free copper, and reaction-bonded silicon carbide (RB-SiC). The cutting performance of the ball endmill was investigated by examining surface roughness and form accuracy of the machined workpiece as well as tool wear characteristics. Micro-dimple arrays, micro-grooves, and micro-pyramid arrays with extremely smooth surface and high-accuracy profile could be obtained on oxygen-free copper without remarkable tool wear. When machining RB-SiC, however, tool flank wear takes place, leading to a rough surface finish. After the tool has worn off, the cutting performance of the endmill significantly depended on the tool feed direction. The optimum tool feed direction for micro-grooving was experimentally investigated.     

The investigation of mechanism of serrated chip formation under different cutting speeds

Chip type is determined by the coupled effects of workpiece material property, cutting speed, uncut chip thickness, feed rate, and tool edge geometry. The understanding of chip formation plays a critical role in studying surface integrity and optimization of machining process variables. Serrated chip, one of the major important chip type, is usually formed in hard cutting at high speed. In this study, a new analytical model has been proposed to better understand the formation of serrated chip, and the simulations have been acquired using ABAQUS/Explicit in machining AISI 1045 during different speeds (from 60 to 6000 m/min). The workpiece material property is modeled with the Johnson-Cook model, and the experiments have been conducted with AISI 1045 during speeds from 60 to 1200 m/min. It has been shown that flow stress is influenced simultaneously by the strain rate hardening and temperature softening. When the speed reaches very high, the temperature softening will fail, and the strain rate hardening will play a more important role. Also, it can be found that the hardening ratio increases when the cutting speed rises. The results of the simulations and experiments correlated well. The cutting force and thrust force both decrease as the cutting speed increases, and the difference between them will shrink when the machining speed reaches a high level.     

An experimental investigation of the influence of cutting parameters on cutting temperature in milling Ti6Al4V by applying semi-artificial thermocouple

An investigation was reported on the cutting temperature in milling Ti6Al4V by applying semi-artificial thermocouple. ANOVA was conducted on the experimental results, and regression models were obtained. Analysis results showed that the tool temperature and workpiece temperature performed a similar rising trend with the increase of cutting parameters, including cutting speed, feed rate, radial feed, and axial feed. And their influence degrees decreased successively. The cutting force with different cutting parameters was also measured, and the relationship between cutting temperature and cutting force was discussed. It was found that cutting temperature and cutting force obtained in the experiment had the same fluctuation feature. Therefore, the cutting force and cutting temperature could complement each other for monitoring and analysis of the cutting process.