Effect of grinding wheel spindle vibration on surface roughness and subsurface damage in brittle material grinding

The external interference and vibration can seriously affect the machining errors in brittle materials grinding process. This paper proposes a new model to analyze the relationship between surface roughness (SR) and subsurface damage (SSD) depth on the basis of grinding kinematics analysis and indentation fracture mechanics of brittle materials taking the wheel spindle vibration into account. The basic equations, for example, equations of grain trajectory and penetration depth are derived in new forms. Based on the basic equations above, the existing SR and SSD formulae are modified for further study. The effects of grinding and vibration parameters on SR and SSD are respectively analyzed in detail. Results show that both SR and SSD increase with the increase of table speed and vibration amplitude resulting in bad surface and subsurface quality. On the other hand, both the increasing grinding speed and decreasing vibration frequency can improve the quality of ground surface and subsurface with small SR and SSD. In addition, the increase of initial grinding depth and vibration initial phase increase the depth of SSD but have little effect on SR. The penetration depth and distance between grain's tip and finished surface are the two main factors considered to cause the different effect laws on SR and SSD among these parameters. Experiment is carried out to validate the rationality of proposed model. The effect trends of various grinding parameters on SR obtained by our model consist with measured experimental data. The typical subsurface crack system is clearly revealed through the experimental observation on SSD using SEM. Finally, the relationship between the two is fitted utilizing quadratic polynomial. Results show that the SSD depth is nonlinear monotone increasing with SR and the fitting accuracy is more or less affected by both grinding and vibration parameters.     

An analysis of grinding power and surface roughness in external cylindrical grinding of hardened SCM440 steel using the response surface method

The aim of this study was to analyze effectively the grinding power spent during the process and the surface roughness of the ground workpiece in the external cylindrical grinding of hardened SCM440 steel using the response surface method. A Hall effect sensor was used for measuring the grinding power of the spindle driving motor. The surface roughness was also measured and evaluated according to the change of the grinding conditions. Response surface models were developed to predict the grinding power and the surface roughness using the experimental results. From adding simply material removal rate to the contour plot of these mathematical models, it was seen that useful grinding conditions for industrial application could be easily determined.     

Relationship between surface roughness and subsurface crack depth during grinding of optical glass BK7

Subsurface damages induced by grinding strongly influence the mechanical strength and optical quality of optical glasses. It is meaningful to rapid evaluate the depth of subsurface cracking through the measurement of surface roughness under different grinding parameters. Based on the features of surface and subsurface cracks as well as the kinetic analysis of surface grinding, the relationship between surface roughness and subsurface crack depth was established. Surface grinding experiments for optical glass BK7 were conducted. Utilizing optical microscope, optical profiling system and polishing-etching technique, the dependence of surface roughness and subsurface crack depth on grinding parameters was systematically analyzed. The predicted model of the relationship between surface roughness and subsurface crack depth was compared with experimental results. It was found that the relationship between surface roughness and subsurface crack depth is influenced by the half apex angle of abrasive grain as well as the magnitude of extra grain extrusion.     

Use of surface roughness measurements to improve the estimation of the heat partition in grinding

In grinding, the heat partition is used to estimate the percentage of energy entering the workpiece which makes it possible to estimate grinding temperatures. In this work, a correlation was observed between surface roughness and the heat partition when grinding 1018 steel with an 80 grit aluminum oxide wheel. This correlation was used to improve the usability of a popular heat partition model by making it easier to estimate the grain radius, which is an important parameter in this model. The grain radius is used to account for the grinding wheel surface topography and is virtually impossible to directly measure in practice. To validate the proposed model, infrared temperature measurements along with 3D finite element simulations were used to determine the heat partition for different dressing conditions and techniques. For the experimental conditions used in this research, the measurements and simulations confirmed that one can use surface roughness to estimate the grain radius. The average difference between the heat partition predicted using the proposed model and the conventional approach was 7.5%, while the resulting maximum grinding temperatures predicted using the proposed model agreed with infrared temperature measurements to within 5%.     

Residual stresses, distortion and surface roughness produced by grinding thin wall ductile iron plates

This work deals with grinding effects on thin wall ductile iron plates. Residual stresses, shape distortion and surface roughness were measured on thin wall plates of different nodule count, ferritised and afterwards dry ground under several grinding conditions. In all cases, tensile residual stresses are maximum at the surface, and their profile decreases with depth until becoming compressive. No phase transformations can be observed at depths of up to 30 μm below surface, although plastic deformation is visible through nodules and grains enlargement. Distortion increases when the depth of cut and nodule count increase and the workspeed decreases. The mean stresses of the profile tensile zone also increase when the nodule count increases. Surface roughness improves slightly as nodule count increases and workspeed decreases. This tendency is more noticeable when depth of cut decreases. The arithmetic mean roughness (Ra) values obtained were always below 0.8 μm.     

Study on surface roughness model and surface forming mechanism of ceramics in quick point grinding

The quick-point grinding experiment of fluorophlogopite was conducted by using a MK9025A profile grinder which considered the simple single factor, such as the grinding wheel and table feed speed, grinding depth, inclining angle and deflection angle. The experimental results indicated that the surface roughness was mainly influenced on inclining angle and deflecting angle. Moreover, the modified model of the quick-point grinding process was proposed in the paper, which based on Malkin kinematics model, Snoeys empirical model and grinding thickness empirical model. The inclining angle and deflecting angle was introduced in the modified model. Comparison of the predicted results of these models and experimental ones indicated that the modified model was in well agreement with the experimental data. Further, standard deviation of these models and experiment was studied in the paper, it is found that the modified model was the more ideal. In order to study the effect of various technology factors on the sensitivity of surface roughness, “Relative extremum error” concept was first proposed in the paper. It was found that simple single factor in the modified model were relatively sensitive to surface roughness than other models.     

Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks

In machining of parts, surface quality is one of the most specified customer requirements. Major indication of surface quality on machined parts is surface roughness. Finish hard turning using Cubic Boron Nitride (CBN) tools allows manufacturers to simplify their processes and still achieve the desired surface roughness. There are various machining parameters have an effect on the surface roughness, but those effects have not been adequately quantified. In order for manufacturers to maximize their gains from utilizing finish hard turning, accurate predictive models for surface roughness and tool wear must be constructed. This paper utilizes neural network modeling to predict surface roughness and tool flank wear over the machining time for variety of cutting conditions in finish hard turning. Regression models are also developed in order to capture process specific parameters. A set of sparse experimental data for finish turning of hardened AISI 52100 steel obtained from literature and the experimental data obtained from performed experiments in finish turning of hardened AISI H-13 steel have been utilized. The data sets from measured surface roughness and tool flank wear were employed to train the neural network models. Trained neural network models were used in predicting surface roughness and tool flank wear for other cutting conditions. A comparison of neural network models with regression models is also carried out. Predictive neural network models are found to be capable of better predictions for surface roughness and tool flank wear within the range that they had been trained.Predictive neural network modeling is also extended to predict tool wear and surface roughness patterns seen in finish hard turning processes. Decrease in the feed rate resulted in better surface roughness but slightly faster tool wear development, and increasing cutting speed resulted in significant increase in tool wear development but resulted in better surface roughness. Increase in the workpiece hardness resulted in better surface roughness but higher tool wear. Overall, CBN inserts with honed edge geometry performed better both in terms of surface roughness and tool wear development.     

A probabilistic approach to predict surface roughness in ceramic grinding

The quality of the surface produced during ceramic grinding is important as it influences the performance of the finished part to great extent. Hence, the estimation of surface roughness can cater to the requirements of performance evaluation. But, the surface finish is governed by many factors and its experimental determination is laborious and time consuming. So the establishment of a model for the reliable prediction of surface roughness is still a key issue for ceramic grinding. In this study, a new analytical surface roughness model is developed on the basis of stochastic nature of the grinding process, governed mainly by the random geometry and the random distribution of cutting edges. This model has been validated by the experimental results of silicon carbide grinding. The theoretical analysis yielded values which agree reasonably well with the experimental results.     

A review of surface roughness generation in ultra-precision machining

Ultra-precision machining (UPM) is capable of manufacturing a high quality surface at a nanometric surface roughness. For such high quality surface in a UPM process, due to the machining complexity any variable would be possible to deteriorate surface quality, consequently receiving much attention and interest. The general factors are summarized as machine tool, cutting conditions, tool geometry, environmental conditions, material property, chip formation, tool wear, vibration etc. This paper aims to review the current state of the art in studying the surface roughness formation and the factors influencing surface roughness in UPM. Firstly, the surface roughness characteristics in UPM is introduced. Then in UPM, a wide variety of factors for surface roughness are then reviewed in detail and the mechanism of surface roughness formation is concluded thoroughly. Finally, the challenges and opportunities faced by industry and academia are discussed and several principle conclusions are drawn.     

几种因素对快速点磨削表面粗糙度的影响

分析了点磨削加工表面形貌及其精度的几种影响因素.研究发现:砂轮速度和磨削深度对表面粗糙度的影响都可归结为未变形切屑厚度的改变.减小点磨削倾斜角,可以减小未变形切屑厚度,从而得到理想的表面粗糙度.加大磨削深度和轴向进给量可提高材料去除率,但会造成粗糙度增大.这可归结为砂轮有效磨粒数的减少导致工件的表面粗糙度降低.点磨削通过改变倾斜角大小来增加参与磨削的有效磨粒数,保证高材料去除率的同时获得良好表面质量.增加光磨次数和应用倾斜型砂轮都增加了磨粒和工件表面轮廓突峰的接触次数,对于改善表面粗糙度十分有益.     

Predicting surface roughness in machining: a review

The general manufacturing problem can be described as the achievement of a predefined product quality with given equipment, cost and time constraints. Unfortunately, for some quality characteristics of a product such as surface roughness it is hard to ensure that these requirements will be met. This paper aims at presenting the various methodologies and practices that are being employed for the prediction of surface roughness.The resulting benefits allow for the manufacturing process to become more productive and competitive and at the same time to reduce any re-processing of the machined workpiece so as to satisfy the technical specifications. Each approach with its advantages and disadvantages is outlined and the present and future trends are discussed. The approaches are classified into those based on machining theory, experimental investigation, designed experiments and artificial intelligence (AI).     

Conservation law of surface roughness in single point diamond turning

In this work, a comprehensive model is established to predict the surface roughness achieved by single point diamond turning. In addition to the calculation of the roughness components in relation to the kinematics and minimum undeformed chip thickness, the newly developed model also takes the effects of plastic side flow and elastic recovery of materials as machined into account. Moreover, the ‘size effect’ has also been successfully integrated into the model, i.e. an inflection point appears in the trend line of predicted surface roughness as the ratio of maximal undeformed chip thickness to cutting edge radius (h_Dmax/r_n) is equal to one unit. Face turning experiments validate that the maximal prediction error is only 13.35%. As the ratio of h_Dmax/r_n is higher than one unit, both the prediction and experiments reveal that a conservation law exists in diamond turned surface roughness, owing to the competitive effects of kinematics, minimum undeformed chip thickness, plastic side flow and elastic recovery of materials on surface formation. Under the conservation law, the freedom control for an invariable surface roughness can be fulfilled in response to a quantitative ratio of h_Dmax/r_n, either through an accurate configuration of feed rate and depth of cut with fixed tool nose radius and cutting edge radius, or by a reasonable selection of tool nose radius and controlled cutting edge radius with designed feed rate and depth of cut.     

Surface and geometry error modeling in brittle mode grinding of ophthalmic lenses moulds

The selection of modeling and machining parameters for glass mould fabrication in ophthalmic lenses production, has required the definition of a theoretical–empirical model of the ground surface in order to predict the overall geometry errors of the surface. The accurate control of the geometrical errors and of the surface texture for the mould functional surface is crucial for the subsequent polishing operation, which is responsible for the final geometry, surface finish and cost. The basic hypotheses validation has been accomplished by measuring the micro-geometric parameters P, W and R and by characterizing the macro-geometry comparing the nominal profile and the measured profile. The correspondence among theoretical hypotheses and experimental results allows realistic predictions of the attainable surface texture during a contour grinding operation and the adoption of preventive actions in order to compensate the geometrical errors due to modeling and tool path generation parameters.     

A study on surface grinding of 300 mm silicon wafers

Most of today's IC chips are made from 200 mm or 150 mm silicon wafers. It is estimated that the transition from 200 mm to 300 mm wafers will bring a die cost saving of 30–40%. To meet their customers' needs, silicon wafer manufacturers are actively searching for cost-effective ways to manufacture 300 mm wafers with high quality. This paper presents the results of a study on surface grinding of 300 mm silicon wafers. In this study, a three-factor two-level full factorial design is employed to reveal the main effects as well as the interaction effects of three process parameters (wheel rotational speed, chuck rotational speed and feedrate). The process outputs studied include spindle motor current, surface roughness, grinding marks and depth of subsurface cracks.     

Generalized practical models of cylindrical plunge grinding processes

This paper presents generalized grinding process models developed for cylindrical grinding processes based on the systematic analysis and experiments. The generalized model forms are established to maintain the same model structures with a minimal number of parameters so that the model coefficients can be determined through a small number of experiments when applied to different grinding workpiece materials and wheels. The relationships for power, surface roughness, G-ratio and surface burning are established for various steel alloys and alumina grinding wheels. It is shown that the established models provide good predictive capabilities while maintaining simple structures.     

Experimental study on grinding force and grinding temperature of Aermet 100 steel in surface grinding

This paper investigates grinding force and grinding temperature of ultra-high strength steel Aermet 100 in conventional surface grinding using a single alumina wheel, a white alumina wheel and a cubic boron nitride wheel. First, mathematical models of grinding force and grinding temperature for three wheels were established. Then, the role of chip formation force and friction force in grinding force was investigated and thermal distribution in contact zone between workpiece and wheel was analyzed based on the mathematical model. The experimental result indicated that the minimum grinding force and the maximum grinding force ratio under the same grinding parameters can be achieved when using a CBN wheel and a single alumina wheel, respectively. When the phenomenon of large grinding force and high grinding temperature appeared, the workpiece material would adhere locally to the single alumina wheel. Grinding temperature was in a high state under the effect of two main aspects: poor thermal properties of grinding wheel and low coolant efficiency. The predicted value of grinding force and grinding temperature were compared with those experimentally obtained and the results show a reasonable agreement.     

Research on the fractal of surface topography of grinding

Fractal theory is widely used in analysing the topography of machined surfaces. In this paper, the formula that describes the relation between the fractal dimension D and R_a or R_q or S_m of surface roughness of different ground surfaces is obtained by measuring ground surfaces and researching the fractal features of them. Using a computer, a theoretical basis is built for the fractal simulation of the ground surface.     

Modeling surface roughness in the stone polishing process

In this paper, a new method for modeling and predicting the surface roughness of the workpiece in the stone polishing process is developed. This method is based on the random distribution of the stone grain protrusion heights and the force balance by contact grains. To do so, first, the topography of a polishing stone is generated based on a Gaussian distribution with the mean value and standard deviation determined from a given stone grit number. Second, the plasticity theory is applied to determine the micro depth of cut of a single grain for a given workpiece hardness (Brinell number). Third, a search method is developed to determine the number of the contact grains and the micro depth of cut, based on the force balance principle between the force applied on the stone and the forces transmitted to the grains that are in contact with the workpiece. Fourth, a method is presented for predicting the surface roughness based on the micro depth of cut and contact grains. A good agreement of the prediction results with the experimental data proves the effectiveness of the proposed method.     

Finite element modeling of the surface roughness of 5052 Al alloy subjected to a surface severe plastic deformation process

The surface of 5052 Al alloy plates is severely plastically deformed via multiple impacts by high-velocity tungsten carbide/cobalt (WC/Co) balls in a surface nanocrystallization and hardening (SNH) process. The surface roughness of 5052 Al alloy plates as a function of the impacting ball size and processing time has been evaluated via non-contact 3D profilometry. A three-dimensional finite element (FE) model has been developed to simulate the formation of peaks and valleys during the SNH process. The peak-to-valley distance predicted from the FEM matches the maximum PV value measured experimentally quite well, indicating that surface roughening of 5052 Al alloy plates during the SNH process using WC/Co balls is mainly dictated by the indentation process of the impacting balls. The implications of this surface roughening mechanism in the final surface roughness, processing time, related microstructure change, and property alteration are discussed.     

Correlating surface roughness and vibration on plunge cylindrical grinding of steel

Since the wear of a grinding wheel has a direct effect on the workpiece vibration and both have effect on the workpiece quality, the main goal of this work is to study the relation between the process vibration signals and the workpiece quality (mean roughness, circularity and burning) as the grinding wheel gets worn, in an attempt to use these signals to decide the exact moment to dress the wheel. In order to reach this goal, several experiments were carried out in a plunge cylindrical grinding operation of an AISI 52100 quenched and tempered steel, having as input variables the dressing overlap ratio, the spark out time and the workpiece velocity. The output variables were the workpiece surface roughness and circularity and also the process vibration during both, the cutting phase and the spark out phase of the grinding cycle. The main conclusions were: (1) it is possible to have good workpiece quality even with a vibration level much higher than that obtained with a recently dressed wheel; (2) vibration during cutting phase and at the end of complete spark out can be used to monitor the wheel condition at least when high dressing overlap ratio is used; and (3) the decrease in the spark out time makes the vibration at the end of spark out increase a lot, but does not cause such a damage in surface roughness. This fact makes the use of partial spark out feasible in some situations.