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.     

Optimum selection of abrasive flow machining conditions during fine finishing of Al/15 wt% SiC-MMC using Taguchi method

Abrasive flow machining (AFM) is gaining widespread application finishing process on difficult to reach surfaces in aviation, automobile, and tooling industry. Al/SiC_p-MMC is a promising material in these industries. Here, AFM has been used to finish conventionally machined cylindrical surface of Al/15 wt% SiC_p-MMC workpiece. This paper presents the utilization of robust design-based Taguchi method for optimization of AFM parameters. The influences of AFM process parameters on surface finish and material removal have been analyzed. Taguchi experimental design concept, L₁₈ (6¹?×?3⁷) mixed orthogonal array is used to determine the S/N ratio and optimize the AFM process parameters. Analysis of variance and F test values also indicates the significant AFM parameters affecting the finishing performance. The mathematical models for R _a, R _t, ΔR _a, and ΔR _t and material removal are established to investigate the influence of AFM parameters. Conformation test results verify the effectiveness of these models and optimal parametric combination within the considered range. Scanning electron micrographs testifies the effectiveness of AFM process in fine finishing of Al/15 wt% SiC_p-MMC.     

Modeling of abrasive flow rotary machining process by artificial neural network

Abrasive flow machining (AFM) is one of the non-traditional machining processes applicable to finishing, deburring, rounding of edges, and removing defective layers from workpiece surface. Abrasive material, used as a mixture of a polymer with abrasive material powder, has reciprocal motion on workpiece surface under pressure during the process. In the following study, a new method of AFM process called henceforth abrasive flow rotary machining (AFRM) will be proposed, in which by elimination of reciprocal motion of abrasive material and the mere use of its stirring and rotation of workpiece, the amount of used material would be optimized. Furthermore, AFRM is executable by simpler tools and machines. In order to investigate performance of the method, experimental tests were designed by the Taguchi method. Then, the tests were carried out and the influence of candidate effective parameters was determined and modeled by artificial neural network (ANN) method. To evaluate the ANN results, they were compared with reported results of AFM. An agreement between our ANN results on predictions of AFRM material removal value and surface roughness was observed with AFM data. The results showed through AFRM, in addition to saving of abrasive material, surface finish is achievable same as AFM’s.     

ON THE PERFORMANCE ANALYSIS OF FLEXIBLE MAGNETIC ABRASIVE BRUSH

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.     

Effect of material microstructure and tool geometry on surface generation in single point diamond turning

There is a strong desire in industry to improve surface finish when performing ultra-precision, single point diamond turning (SPDT) to reduce the amount of post process polishing required to meet final product specifications. However there are well known factors in SPDT which limit achievable surface finish. This paper focuses on the role of material microstructure, including grain boundary density and the presence of inclusions, as well as tool design on surface roughness using the concept of size effect. Size effect can be described as an interplay between the material microstructure dimension and the relative size of the uncut chip thickness with respect to the cutting edge radius. Since one of the controllable parameters in size effect is grain size and dislocation density, controlled studies were performed on samples whose microstructure was refined by mechanical strain hardening through rolling and a friction stir process (FSP). The use of the ultra-fine grained workpiece prepared using an FSP was observed to reduce side flow as well as grain boundary and inclusion induced roughness. The role of tool geometry on material induced roughness was investigated using a tool with a rounded primary cutting edge and a flat secondary edge. The use of the flat secondary edge was observed to improve surface finish when machining a flat surface. This improvement was primarily attributed to a reduction in side flow and material microstructural effects. By combining these approaches an average surface roughness R_a value of 0.685 nm was achieved when SPDT a flat surface. Furthermore the custom tool has the potential to significantly improve the productivity of SPDT by allowing for a much higher feed rate while still achieving a high quality surface finish.     

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.     

NANO-FINISHING OF STAINLESS-STEEL TUBES USING ROTATIONAL MAGNETORHEOLOGICAL ABRASIVE FLOW FINISHING PROCESS

A new polishing method called Rotational (R)-Magnetorheological Abrasive Flow Finishing (MRAFF) process has been proposed by rotating a magnetic field applied to the Magnetorheological polishing (MRP) medium in addition to the reciprocating motion provided by the hydraulic unit to finish internal surface of cylindrical stainless steel (non-magnetic) workpiece. By intelligently controlling these two motions uniform smooth mirror-like finished surface in the range of nm has been achieved. For parametric analysis of the process, the experiments have been planned using design of experiments technique and response surface regression analysis is performed to analyze the effects of process parameters on finishing performance. Analysis of Variance (ANOVA) is conducted and contribution of each model term affecting percent improvement in surface finish is calculated. The experimental results are discussed and optimum finishing conditions are identified from optimization study. The present study shows that rotational speed of the magnet has most significant effect on output response (percentage improvement in surface roughness, %ΔR _a ). The best surface finish obtained on stainless steel workpiece with R-MRAFF process is 16 nm.     

Electrochemical machining analysis on grid cathode composed of square cells

During the electrochemical machining (ECM), the cathodes designed by the existing methods are mainly unitary cathodes, which can be only used to produce the workpieces with the same shapes. However, there are few researches on designing cathodes for machining the different workpieces with the different surfaces. This paper presents the grid cathode composed of the square cells to produce the workpieces with different shapes. Three types of the square cells, 2.5 mm′2.5 mm, 3 mm′3 mm, and 4 mm′4 mm, are utilized to construct the plane, the slant, and the blade cathode. The material of the cathode and the anode is CrNi 18 Ti 9 , and the ingredient of electrolyte is 15% NaCl and 15% NaNO 3 . The machining equilibrium machining current and time are acquired and analyzed, the machining process and the workpiece quality are compared between using the grid cathode and the unitary cathode. Moreover, the machining errors on the workpiece surface are measured and analyzed, and the error reasons are traced and discussed to obtain the better surface quality of the workpiece. The experiment and analysis results show that the grid cathode can be used to manufacture the workpieces with complex shapes in certain range of the error. The workpiece quality improves with the size of the square cell being reduced, and if the square element is small enough, the workpiece quality is almost equal to the one machined by the unitary cathode. The proposed research realizes a single cathode machining the different workpieces with the different surfaces.     

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.     

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.     

Self-tuning fuzzy control with a grey prediction for wire rupture prevention in WEDM

Wire rupture in the wire electrical discharge machining (WEDM) process is one of the most troublesome problems in practical applications. In this paper, the abnormal ratio R_ab, defined as the proportion of abnormal sparks in a sampling period, is taken to represent the gap state in machining. The grey predictor is adopted to compensate the time-delayed R_ab caused by the low pass filter data processing. A gain self-tuning fuzzy control system has been developed to cope with the conditions that often occur with wire rupture in the WEDM process, such as an improper setting of machining parameters, machining the workpiece with varying thickness, etc. Experimental results of several cases show that the proposed controller results in a satisfactory performance. Not only can it immediately suppress transient situation once there is a sudden change of workpiece thickness, but a stable performance can also be achieved during machining a workpiece of constant thickness. As a result, wire rupture problems in most WEDM processes can be successively solved by the proposed control strategy.     

Image processing for chatter identification in machining processes

Identifying chatter or intensive self-excited relative tool–workpiece vibration is one of the main challenges in the realization of automatic machining processes. Chatter is undesirable because it causes poor surface finish and machining accuracy, as well as reducing tool life. The identification of chatter is performed by evaluating the surface roughness of a turned workpiece undergoing chatter and chatter-free processes. In this paper, an image-processing approach for the identification of chatter vibration in a turning process was investigated. Chatter is identified by first establishing the correlation between the surface roughness and the level of vibration or chatter in the turning process. Images from chatter-free and chatter-rich turning processes are analyzed. Several quantification parameters are utilized to differentiate between chatter and chatter-free processes. The arithmetic average of gray level G _a is computed. Intensity histograms are constructed and then the variance, mean, and optical roughness parameter of the intensity distributions are calculated. The surface texture analysis is carried out on the images using a second-order histogram or co-occurrence matrix of the images. Analysis is performed to investigate the ability of each technique to differentiate between a chatter-rich and a chatter-free process. Finally, a machine vision system is proposed to identify the presence of chatter vibration in a turning process.     

Performance and surface alloying characteristics of Cu–Cr and Cu–Mo powder metal tool electrodes in electrical discharge machining

The main objective of this study is to investigate the effect of Cu–Cr and Cu–Mo powder metal (PM) tool electrodes on electrical discharge machining (EDM) performance outputs. The EDM performance measures used in the study are material removal rate (MRR), tool electrode wear rate (EWR), average workpiece surface roughness (R_a), machined workpiece surface hardness, abrasive wear resistance, corrosion resistance, and workpiece alloyed layer depth and composition. The EDM performance of Cu–Cr and Cu–Mo PM electrodes produced at three different mixing ratios (15, 25, and 35 wt% Cr or Mo), compacting pressures (P_c = 600, 700, and 800 MPa), and sintering temperatures (T_s = 800, 850, and 900 °C) are compared with those machined with electrolytic Cu and Cu PM electrodes when machining SAE 1040 steel workpiece. Analyses revealed that tool materials were deposited as a layer over the work surface yielding high surface hardness, strong abrasion, and corrosion resistance. Moreover, the mixing ratio, P_c, and T_s affect the MRR, EWR, and R_a values.     

Modeling of machined surface characteristics in cryogenic orthogonal turning of inconel 718

The determination of the optimal machining conditions for assuring desired machined surface characteristics of a part is one of the main goals in a machining process. In this article, the impact of a cooling lubrication fluid, its delivery phase and location, as well as machining parameters, on residual stresses have been investigated. The workpiece material under observation is Inconel 718. For measuring residual stress profiles, X-ray diffraction technique has been used. Additionally, besides the experimental work, modeling with the finite element method model was implemented and correlated with experimental results. The results show that residual stresses are influenced by the cooling lubrication scenario, even though the machining parameters are kept constant. However, flood and cryogenic machining show more compressive residual stresses than a dry machining case. On the other hand, the results have shown also that machining parameters influence residual stresses, where stresses increase with their increase (v_c and f).     

Performance Analysis of Wire Electrodes on Machining Ti-6Al-4V Alloy using Electrical Discharge Machining Process

High-strength materials with complex shapes can be easily machined by electrical discharge machining process. In the present study, an attempt has been made to analyze the influence of wire electrode on Kerf width and workpiece surface roughness in wire EDM process. Due to its importance in the aircrafts and automobiles, Ti-6Al-4V alloy has been chosen as the workpiece material. The various experiments have been conducted based on a Taguchi L₉ orthogonal array with various types of wire electrodes, such as conventional brass wire, zinc-coated wire and diffused coated brass wire. From the experimental results, it has been observed that diffused coated wire produced better surface finish with minimum kerf width compared to the other two wire electrodes. It has also been observed that the pulse off-time has more influent nature on machining characteristics such as surface roughness and kerf width.     

Investigation on surface finish and metallic particle emission during machining of aluminum alloys using response surface methodology and desirability functions

The surface finish of a mechanical part plays an important role as it determines the part’s field performance. The machining parameters and conditions governing the part surface finish also impact on the other machining process performance indicators such as tool wear, tool life, cycle time, machining cost, and undesirable emissions of aerosols and metallic particles. In today’s metal cutting industry, a major concern is the occupational safety and health hazard associated with cutting fluids usage and metallic particle emission. It is therefore necessary to determine machining conditions that could improve the part surface finish while maintaining low the aerosol emission. In this research study, statistical methods are used to study the surface finish parameters and the metallic particle emissions during milling of aluminum alloys (6061-T6, 7075-T6, and 2024-T351) with two coated carbide tools (TiCN and a multilayer TiCN?+?Al₂O₃?+?TiN). Following an implementation of multilevel design of experiment, machining trials and determination of mains most influential factors, surface responses and desirability functions are used to determine the best process operational conditions and windows. The results of this research demonstrate that TiCN-coated tool generates fewer respirable airborne particles during machining than multilayers TiCN?+?Al₂O₃?+?TiN-coated tool. Overall, it is shown that the use of TiCN coating tool provides a better opportunity for an environmentally benign dry machining along with improvement on surface quality.     

Improved measure of workpiece surface deterioration during turning using non-contact vision method

The surface finish quality of a machined workpiece is commonly measured using the average roughness parameter, R_a. This parameter, however, is insensitive to the lateral changes undergone by the surface in the feed direction as a consequence of tool wear. In this work, the effectiveness of four methods of workpiece surface analysis, namely autocorrelation, cross-correlation, and two new methods, called lateral material shift (LMS) ratio and profile slope ratio (PSR) analyses are investigated. Dry machining experiments were carried out on 316 stainless steel. Images of tool nose and workpiece profiles were captured using digital camera, and the edges were extracted using sub-pixel edge detection. In the autocorrelation approach, each workpiece profile was correlated with a shifted version of the same profile. In the cross-correlation approach, the workpiece profiles at different stages of machining were correlated with a reference profile generated using the unworn tool edge. In the LMS ratio method, the material shift ratios were determined from each waveform on the workpiece profile at various stages of tool wear, while in the PSR method the slopes at the right and left part of the waveform were compared. Among the four methods, the LMS ratio method produced the best correlation with tool flank wear with the maximum R-squared value of 0.9461, while average roughness R_a showed no correlation at all with both major and nose flank wear.     

The tribology of orthogonal finish machining — A review

A review of orthogonal finish machining is presented. The relations be- tween material flow conditions in the three distinct flow regions in metal cutting are examined: the deformation zone governs chip flow, the tool-chip contact zone is responsible for tool wear and the tool base rubbing zone controls workpiece integrity. In orthogonal machining the initial sharp tool cutting edge is of importance regarding the integrity of surface finish although tool edge forces have been the subject of more investigations. Material flow near the tool edge is considered with respect to the author's own model.     

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.     

Simplified stiffness model for spherical rough contacts

Abstract

Obtaining a surface with negligible roughness is very expensive, time consuming and unnecessary. The influence of surface roughness on the contact stiffness is of great importance. The extra cost associated with unnecessary surface finish can be limited by eliminating the unnecessary machining operations beyond the required surface finish. In this article, a simplified solution is presented to calculate the stiffness of rough contact between the workpiece and spherical locator; also, the effect of surface roughness on the stiffness and deformation of rough spherical contact is studied for different applied loads to find an ‘economic roughness’ under machining forces.