ABRASIVE FLOW MACHINING WITH ADDITIONAL CENTRIFUGAL FORCE APPLIED TO THE MEDIA

Abrasive flow machining (AFM) is one of the important non-traditional metal finishing technologies which was introduced during the late 1960s. The process has found applications in a wide range of fields such as aerospace, defence, surgical and tool manufacturing industries. Recently, an effort has been made towards the performance improvement of this process by applying centrifugal force on the abrasive media with the use of a rotating centrifugal force generating (CFG) rod introduced in the workpiece passage. The results have been encouraging. The present paper discusses the results of changing the parameters like shape and rotational speed of CFG rod, extrusion pressure, number of process cycles and abrasive grit size. The results indicate that all the input variables have significant effect on the response parameters, which for the present study were taken as material removal and surface roughness. An analytical model is proposed for the velocity and the angle at which abrasive particles attack the workpiece surface in the process.     

ABRASIVE FLOW MACHINING WITH ADDITIONAL CENTRIFUGAL FORCE APPLIED TO THE MEDIA

Abrasive flow machining (AFM) is one of the important non-traditional metal finishing technologies which was introduced during the late 1960s. The process has found applications in a wide range of fields such as aerospace, defence, surgical and tool manufacturing industries. Recently, an effort has been made towards the performance improvement of this process by applying centrifugal force on the abrasive media with the use of a rotating centrifugal force generating (CFG) rod introduced in the workpiece passage. The results have been encouraging. The present paper discusses the results of changing the parameters like shape and rotational speed of CFG rod, extrusion pressure, number of process cycles and abrasive grit size. The results indicate that all the input variables have significant effect on the response parameters, which for the present study were taken as material removal and surface roughness. An analytical model is proposed for the velocity and the angle at which abrasive particles attack the workpiece surface in the process.     

Study of the rheological properties and the finishing behavior of abrasive gels in abrasive flow machining

Abrasive flow machining (AFM) is an effective method to finish the smooth surface in the complex holes. Abrasive media are key elements which dominate the polished results in AFM. But it is hard to develop the machining model of these abrasive gels because of its complicated mechanism. In this research, a non-Newtonian flow is used to set up the abrasive mechanism of the abrasive media in AFM. Power law is a main equation of the non-Newtonian flow to describe the motion of the abrasive media. Viscosities vs. shear rates of different abrasive gels are used to establish the power law in CFD-ACE⁺ software first. And the working parameters of AFM were applied as input to study the properties of the abrasive gels in AFM. Finally, the relationships between the simulations and the experiments were found. And the abrasive mechanism of the abrasive gels was set up in AFM. The simulated results show that the abrasive gel with high viscosity can entirely deform in the complex hole than the abrasive gel with low viscosity. And the abrasive gel with high viscosity generates a larger shear force than the abrasive gel with low viscosity in the same area. Moreover, the strain rate is seriously changed when the abrasive gel cross over the narrow cross-section of the complex hole. It also means that abrasive gel will produce large finish force in that area. And these results indeed consist with the experiments in AFM.     

Determining dynamically active abrasive particles in the media used in centrifugal force assisted abrasive flow machining process

Abrasive flow machining (AFM) is a relatively new non-traditional process in which a semisolid media consisting of abrasive particles and a flexible polymer carrier is extruded through or across the component to be machine finished. This process is capable of providing excellent surface finishes on a wide range of simple as well as intricated shaped components. Low material removal rate happens to be one major limitation of this process, because during machining not all the abrasive particles participate in removing material from the work piece. Limited efforts have hitherto been directed towards improving the efficiency of the process so as to achieve higher material removal rates. An effort has been made towards the performance improvement of this process by applying centrifugal force on the abrasive media with the use of a rotating centrifugal force generating (CFG) rod introduced in the work piece passage. The modified process is termed as centrifugal force assisted abrasive flow machining (CFAAFM). This paper presents a mathematical model developed to calculate the number of dynamics active abrasive particles participating in the finishing operation in the AFM and CFAAFM process. The analysis of results show that there is great enhancement of number of dynamic active abrasive particles in CFAAFM as compared to the AFM process, which seems to be the contributing factor for the increase in material removal and % improvement in surface roughness for a given number of cycles in CFAAFM. The results of experiments conducted to validate the model show a close agreement between the analytical and experimental results.     

Enhancing AFM process productivity through improved fixturing

Abrasive flow machining (AFM) is a non-conventional finishing process that deburrs and polishes by forcing an abrasive laden media across the workpiece surface. The process embraces a wide range of applications from critical aerospace and medical components to high-production volumes of parts. One serious limitation of this process is its low productivity in terms of rate of improvement in surface roughness. Limited efforts have hitherto been directed towards enhancing the productivity of this process with regard to better quality of workpiece surface. This paper discusses improved fixturing as a technique for productivity enhancement in terms of surface roughness (R _a). A rotating centrifugal-force-generating (CFG) rod is used inside the cylindrical workpiece which provides the centrifugal force to the abrasive particles normal to the axis of workpiece. The effect of the key parameters on the performance of process has been studied. The results shows that for a given improvement in R _a value, the processing time can be reduced by as much as 70–80%. It is seen that the significant process parameters are revolutions per minute of CFG rod, extrusion pressure and abrasive mesh size.     

Morphology and integrity of surfaces finished by centrifugal force assisted abrasive flow machining

Centrifugal force assisted abrasive flow machining (CFAAFM) process has recently been tried as a hybrid machining process with the aim towards performance improvement of assisted abrasive flow machining (AFM) process by applying centrifugal force on the abrasive-laden media with a rotating centrifugal force generating (CFG) rod introduced in the workpiece passage. In the CFAAFM process, the surfaces are generated by erosion from random attack of abrasive grains. CFAAFMed surfaces are unidirectional but random in nature due to transient media flow conditions. In the present paper, surface morphology, surface micro-hardness, X-ray analysis, and surface compressive residual stress produced in the finished surface layer by CFAAFM process is described. The CFAAFM process was performed under different rotational speeds of CFG rod while keeping other input parameters constant during the experiments. The increase in surface microhardness and compressive residual stress of the workpiece with an increase in the rotational speed of CFG rod is attributed to the work-hardening surface that possibly occurs due to ‘throw’ of abrasive particles upon specimen surface.     

基于均匀设计法的磨粒流加工试验

根据磨粒流加工原理,以坦克发动机喷油嘴为研究对象,利用均匀试验设计方法,通过均匀分散而选出较优的磨粒流加工试验参数（磨粒粒径、磨料浓度、加工时间及研磨液的酸碱性）,再通过优化变量得到目标函数,进而获得最优磨粒流加工工艺参数。试验结果表明：采用均匀设计方案较正交设计方案可节省70%的时间;经过均匀试验后,喷油嘴工件内孔表面粗糙度减小,达到了磨粒流加工试验的目的,而回归优化后的工艺参数可以进一步减小喷嘴小孔的内表面粗糙度,所得到表面粗糙度与材料物性及加工时间的数学模型可为磨粒流的生产实际提供技术支持。     

Modeling and Simulation of Cylindrical Electrochemical Magnetic Abrasive Machining Process

Cylindrical Electrochemical Magnetic Abrasive Machining (C-EMAM) is an advanced abrasion-based hybrid machining process that constitutes magnetic abrasive machining and electrochemical dissolution. During the C-EMAM process, a large amount of material is removed from the peaks of the surface irregularities under the simultaneous effect of electrochemical dissolution, abrasion and abrasion-passivation synergism. This article presents the mathematical modeling for material removal and surface roughness during the C-EMAM process. Magnetic potential distribution between the two magnetic poles in which a cylindrical workpiece was placed was calculated using the finite element method. It was further used to find the forces acting on the ferromagnetic particles at contact surfaces. An empirical relation has been also developed considering the effect of electrochemical dissolution and abrasion-passivation synergism based on experiments conducted on a self-developed C-EMAM setup. Finally, a surface roughness model was developed by considering the total volume of material removed with the assumption of a triangular surface profile. The simulated results for material removal and surface roughness were validated using self-conducted experimental results. The computed results were found to be in good agreement with experimental observations.     

砂轮约束磨粒喷射加工表面材料去除机理

基于磨粒特征尺寸与砂轮、工件间液膜厚度比值的变化研究了磨粒喷射光整加工的材料去除机理,建立了两体研磨及三体冲蚀单颗磨粒的材料去除模型和材料去除率模型。试验在MB1332A外圆磨床上完成,加工试样为Sa=06μm左右的45钢。加工表面形貌和微观几何参数分别用SEM和MICROMESVRE2表面轮廓仪测量,试验结果和材料去除模型相吻合。试样表面连续的方向一致的沟槽被随机不连续的微坑所代替,随着加工循环的增加,Sa值由06μm下降到02μm左右。此外,光整加工可以获得各向同性网纹交错的表面,表面轮廓的支撑长度率提高,对工件的耐磨性有利。      

EVALUATION OF RHEOLOGICAL PROPERTIES OF MEDIUM FOR AFM PROCESS

Abrasive Flow Machining (AFM) is a new non-traditional machining process used to deburr, radius, polish, and remove recast layer of components used in a wide range of applications. Material removal in AFM takes place by flowing medium (i.e. carrier/or putty mixed with abrasive particles), across the surface to be machined. The medium is the key element in the process because of its ability to precisely abrade the selected areas along its flow path. From the literature review, it is found that there is a need to study how to evaluate rheological properties of the medium in general, and viscosity in particular. Viscosity of the medium has significant effects on the AFM process performance.

In the present work, effects of concentration and mesh size of abrasive particles, and temperature of medium on the medium viscosity have been studied. To determine the viscosity of the abrasive medium, a viscometer has been designed and fabricated based on the principle of capillary viscometry. Experiments have been conducted at different abrasive concentrations and mesh sizes, and medium temperatures. It is observed from the experiments that the viscosity of the medium increases with the abrasive concentration and decreases with the abrasive mesh size and medium temperature. Theoretical values obtained from mathematical model, and experimental results are compared. The results of viscosity are correlated with the process performance parameters, i.e. material removal and surface roughness. It is observed that there is an increase in material removal and decrease in surface roughness value as viscosity of the medium increases.     

Prediction of surface roughness during abrasive flow machining

An analytical model is proposed to simulate and predict the surface roughness for different machining conditions in abrasive flow machining (AFM). The kinematic analysis is used to model the interaction between grain and workpiece. Fundamental AFM parameters, such as the grain size, grain concentration, active grain density, grain spacing, forces on the grain, initial topography, and initial surface finish (R _a value) of the workpiece are used to describe the grain-workpiece interaction. The AFM process is studied under a systematic variation of grain size, grain concentration and extrusion pressure with initial surface finish of the workpiece. Simulation results show that the proposed model gives results that are consistent with experimental results.     

Temperature as sensitive monitor for efficiency of work in abrasive flow machining

Work efficiency is considered as most concerned target in abrasive flow machining (AFM). It has many influence factors, such as, temperature, media viscosity, abrasive hardness, particles sharpness and density, workpiece hardness, pressure, piston moving speed, etc. The influence of temperature on work efficiency is most critical. In this investigation, both commercial AFM equipment and test rig are used to carry out AFM experiments. AISI1080, 1045 and A36 steels are used as specimens in the tests. It has been shown from AFM tests that media viscosity decreases continuously with increasing temperature. Media temperature increases with increasing cycles, which means media viscosity decreases with cycles increasing. AFM tests shows that increasing cycles extensively decrease materials removal and surface roughness decreasing efficiency. When media with different viscosity is used media with high viscosity has more effective material removal efficiency. The high viscosity media to surface roughness improvement is also better than the low viscosity media at the initial several cycle numbers. With further increasing cycles the roughness improvement difference among different media with different viscosity is reduced. It is found from Mooney viscosity–temperature relation of media that temperature rising directly results in the decrease of media viscosity. When work cycles are increased the media temperature is quickly increased. The media viscosity is also decreased dramatically. In order to understand the mechanism of decrease of material removal efficiency with temperature, computational fluid dynamics (CFD) approach is applied to predict the abrasive particles movement tendency. A two-dimensional model is constructed for AFM process. The simulation results show that the temperature rising of media results in increasing the rolling tendency of abrasive particles which causes work efficiency deteriorated.     

MULTI-OBJECTIVE OPTIMIZATION OF ABRASIVE FLOW MACHINING PROCESSES USING POLYNOMIAL NEURAL NETWORKS AND GENETIC ALGORITHMS

Abrasive flow machining (AFM) is an economic and effective non-traditional machining technique, which is capable of providing excellent surface finish on difficult to approach regions on a wide range of components. With this method, it has become possible to substitute various time-consuming deburring and polishing operations that had often lead to non-reproducible results. In this paper, group method of data handling (GMDH)-type neural networks and Genetic algorithms (GAs) are first used for modelling of the effects of number of cycles and abrasive concentration on both material removal and surface finish, using some experimentally obtained training and testing data for brass and aluminum. Using such polynomial neural network models obtained, multi-objective GAs (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism are then used for Pareto-based optimization of AFM considering two conflicting objectives such as material removal and surface finish. It is shown that some interesting and important relationships as useful optimal design principles involved in the performance of AFM can be discovered by the Pareto-based multi-objective optimization of the obtained polynomial models. Such important optimal principles would not have been obtained without the use of both GMDH-type neural network modelling and multi-objective Pareto optimization approach.     

MULTI-OBJECTIVE OPTIMIZATION OF ABRASIVE FLOW MACHINING PROCESSES USING POLYNOMIAL NEURAL NETWORKS AND GENETIC ALGORITHMS

Abrasive flow machining (AFM) is an economic and effective non-traditional machining technique, which is capable of providing excellent surface finish on difficult to approach regions on a wide range of components. With this method, it has become possible to substitute various time-consuming deburring and polishing operations that had often lead to non-reproducible results. In this paper, group method of data handling (GMDH)-type neural networks and Genetic algorithms (GAs) are first used for modelling of the effects of number of cycles and abrasive concentration on both material removal and surface finish, using some experimentally obtained training and testing data for brass and aluminum. Using such polynomial neural network models obtained, multi-objective GAs (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism are then used for Pareto-based optimization of AFM considering two conflicting objectives such as material removal and surface finish. It is shown that some interesting and important relationships as useful optimal design principles involved in the performance of AFM can be discovered by the Pareto-based multi-objective optimization of the obtained polynomial models. Such important optimal principles would not have been obtained without the use of both GMDH-type neural network modelling and multi-objective Pareto optimization approach.     

EVALUATION OF RHEOLOGICAL PROPERTIES OF MEDIUM FOR AFM PROCESS

Abrasive Flow Machining (AFM) is a new non-traditional machining process used to deburr, radius, polish, and remove recast layer of components used in a wide range of applications. Material removal in AFM takes place by flowing medium (i.e. carrier/or putty mixed with abrasive particles), across the surface to be machined. The medium is the key element in the process because of its ability to precisely abrade the selected areas along its flow path. From the literature review, it is found that there is a need to study how to evaluate rheological properties of the medium in general, and viscosity in particular. Viscosity of the medium has significant effects on the AFM process performance.

In the present work, effects of concentration and mesh size of abrasive particles, and temperature of medium on the medium viscosity have been studied. To determine the viscosity of the abrasive medium, a viscometer has been designed and fabricated based on the principle of capillary viscometry. Experiments have been conducted at different abrasive concentrations and mesh sizes, and medium temperatures. It is observed from the experiments that the viscosity of the medium increases with the abrasive concentration and decreases with the abrasive mesh size and medium temperature. Theoretical values obtained from mathematical model, and experimental results are compared. The results of viscosity are correlated with the process performance parameters, i.e. material removal and surface roughness. It is observed that there is an increase in material removal and decrease in surface roughness value as viscosity of the medium increases.     

Forces prediction during material deformation in abrasive flow machining

To study the finishing mechanism of abrasive flow machining (AFM), theoretical model of forces acting on a single grain has been developed. An experimental research has been carried out by measuring the axial force, radial force and active grain density during the AFM process. Results obtained from theoretical model for grain–workpiece interaction during material deformation have been compared with the experimental data of force and active grains obtained during AFM. Scratching experiments have also been carried out to study the mechanism of material removal during the AFM process. The conclusions arrived by the analysis about the presence of rubbing and ploughing is in agreement with the experimental AFM and scratching results.     

ON THE PERFORMANCE ANALYSIS OF FLEXIBLE MAGNETIC ABRASIVE BRUSH

ABSTRACT

Magnetic abrasive finishing (MAF) of alloy steel workpiece with unbounded magnetic abrasive particles (UMAPs) indicates that the surface finish in the range of nanometer can be achieved. Important controllable four process parameters have been identified which are as current to the electromagnet, machining gap, abrasive size (mesh number), and number of cycles. Experiments have been planned using design of experiments technique. Based upon the results of response surface methodology and analysis of variance (ANOVA), it is concluded that magnetic flux density that depends on current to the electromagnet and machining gap, is most influencing parameter followed by grain size and number of cycles. The surface roughness profile generated during the MAF process has been discussed. To understand the cutting mechanism of magnetic abrasive finishing process, scanning electron microscopy (SEM) and atomic force microscopy (AFM) of the machined surfaces have been carried out. The correlation between surface finish and material removal has also been established.     

Simulation of surface generated during abrasive flow finishing of Al/SiCp-MMC using neural networks

Abrasive flow machining (AFM) is a multivariable finishing process which finds its use in difficult to finish surfaces on difficult to finish materials. Near accurate prediction of generated surface by this process could be very useful for the practicing engineers. Conventionally, regression models are used for such prediction. This paper presents the use of artificial neural networks (ANN) for modeling and simulation of response characteristics during AFM process in finishing of Al/SiC_p metal matrix composites (MMCs) components. A generalized back-propagation neural network with five inputs, four outputs, and one hidden layer is designed. Based upon the experimental data of the effects of AFM process parameters, e.g., abrasive mesh size, number of finishing cycles, extrusion pressure, percentage of abrasive concentration, and media viscosity grade, on performance characteristics, e.g., arithmetic mean value of surface roughness (R _a, micrometers), maximum peak–valley surface roughness height (R _t, micrometers), improvement in R _a (i.e., ΔR _a), and improvement in R _t (i.e., ΔR _t), the networks are trained for finishing of Al/SiC_p-MMC cylindrical components. ANN models are compared with multivariable regression analysis models, and their prediction accuracy is experimentally validated.     

软性磨粒流磨粒入射壁面过程及其加工特性研究

针对利用两相流模型无法计算高浓度固—液两相流固相颗粒撞击壁面时颗粒速度的问题,提出一种边界层内颗粒运动轨迹计算模型,基于Mixture两相流模型和Realizable k-ε湍流模型仿真计算结果,通过分析提取颗粒入射前速度、计算边界层厚度、建立边界层内速度场和颗粒运动分析可以得到颗粒撞击壁面时的速度和入射角度。分析加工表面动压力分布和磨粒体积分数分布,结合两种结构约束流道验证仿真结果与加工效果的对应关系。通过对试验结果的分析,为约束模块的设计提供依据。研究结果表明:磨粒入射速度、磨粒体积分数和加工表面所受动压力大小直接影响工件加工效果,并与材料去除量成正相关关系;在本次试验中选择的工艺参数导致加工材料去除量小,适合初始粗糙度低的工件表面加工,对于此次试验的初始粗糙度应在0.2μm以下;约束模块的设计除了要考虑磨粒流流场特性之外,还要对加工表面的原始加工痕迹作详细了解,为约束模块的设计及加工工艺参数提供参考。     

钛合金曲面磨粒流加工扰流流道仿真与试验研究

针对具有复杂曲面的钛合金工件磨粒流抛光后表面粗糙度Ra不均匀问题,提出一种具有扰流结构的仿型约束加工流道。借助计算流体动力学（CFD）分析软件,结合SST k-ω湍流模型、离散相模型（DPM）和Oka冲蚀模型,仿真分析原始流道和5种不同扰流角度的扰流流道内磨粒流动力学特性。数值模拟结果表明：扰流流场中的磨粒流相较于原始流场在工件表面具有更大的湍流动能、动压力和冲蚀速率,其中扰流角度为30°时冲蚀均匀性较好。基于仿真条件搭建了磨粒流加工试验平台,使用原始流道和30°扰流流道分别进行了加工试验。试验结果表明：使用原始流道加工5 h后,工件表面曲率不同区域的表面粗糙度Ra值分散,加工效果均匀性较差;使用扰流流道加工5 h后,工件表面各区域表面粗糙度Ra的均匀性明显优于无扰流流场的加工均匀性。