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.     

A theoretical and experimental investigation of surface roughness formation in ultra-precision diamond turning

In this paper, a model-based simulation system is presented for the analysis of surface roughness generation in ultra-precision diamond turning. The system is based on a surface roughness model which takes into account the effect of tool geometry, process parameters and relative tool-work vibration. It is evaluated through a series of cutting experiments. The results indicate that the system can predict well the surface roughness profile and the roughness parameters of a diamond turned surface under various cutting conditions. With the use of the spectrum analysis techniques, the system can also help to analyze the effect of vibration on the surface quality of workpiece and to diagnose the machine faults. The potential application of the system in process optimization is also discussed in the text.     

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.     

晶体材料车削表面粗糙度的实验研究

本文探讨了晶体材料的切削加工性，重点分析了切削条件对表面粗糙度的影响。     

Characterisation of nanosurface generation in single-point diamond turning

This paper describes a parametric analysis of nanosurface generation in single-point diamond turning (SPDT). The properties of the surface roughness profiles were extracted and analysed using the power spectrum analysis method. A series of face cutting experiments was undertaken on an aluminium alloy under various cutting conditions. The results indicate that the power spectrum of a surface roughness profile is basically composed of several periodical components that can be correlated to different process parameters and mechanisms of surface generation. Moreover, it is found that the tool feed, tool geometry, spindle error motions and relative vibration between the tool and the workpiece are not the only dominant components contributing to the surface generation in SPDT. Materials swelling and tool interference are other important factors. Based on these findings, relationships are proposed to explain the influence of tool interference on the variation of the spectral components and process parameters. The implications of these findings on the optimisation of the surface quality in SPDT are also discussed.     

Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool

The present work concerns an experimental study of hard turning with CBN tool of AISI 52100 bearing steel, hardened at 64 HRC. The main objectives are firstly focused on delimiting the hard turning domain and investigating tool wear and forces behaviour evolution versus variations of workpiece hardness and cutting speed. Secondly, the relationship between cutting parameters (cutting speed, feed rate and depth of cut) and machining output variables (surface roughness, cutting forces) through the response surface methodology (RSM) are analysed and modeled. The combined effects of the cutting parameters on machining output variables are investigated while employing the analysis of variance (ANOVA). The quadratic model of RSM associated with response optimization technique and composite desirability was used to find optimum values of machining parameters with respect to objectives (surface roughness and cutting force values). Results show how much surface roughness is mainly influenced by feed rate and cutting speed. Also, it is underlined that the thrust force is the highest of cutting force components, and it is highly sensitive to workpiece hardness, negative rake angle and tool wear evolution. Finally, the depth of cut exhibits maximum influence on cutting forces as compared to the feed rate and cutting speed.     

Adhesion analysis and dry machining performance of CVD diamond coatings deposited on surface modified WC-Co turning inserts

This paper investigates the effects of different surface pretreatments on the adhesion and performance of CVD diamond coated WC-Co turning inserts for the dry machining of high silicon aluminum alloys. Different interfacial characteristics between the diamond coatings and the modified WC-Co substrate were obtained by the use of two different chemical etchings and a CrN/Cr interlayer, with the aim to produce an adherent diamond coating by increasing the interlocking effect of the diamond film, and halting the catalytic effect of the cobalt present on the cemented carbide tool. A systematic study is analyzed in terms of the initial cutting tool surface modifications, the deposition and characterization of microcrystalline diamond coatings deposited by HFCVD synthesis, the estimation of the resulting diamond adhesion by Rockwell indentations and Raman spectroscopy, and finally, the evaluation of the dry machining performance of the diamond coated tools on A390 aluminum alloys. The experiments show that chemical etching methods exceed the effect of the CrN/Cr interlayer in increasing the diamond coating adhesion under dry cutting operations. This work provided new insights about optimizing the surface characteristics of cemented carbides to produce adherent diamond coatings in the dry cutting manufacturing chain of high silicon aluminum alloys.     

A study of materials swelling and recovery in single-point diamond turning of ductile materials

This paper presents an investigation of the effect of materials swelling in ultra-precision machining of ductile materials. The combined influence of materials swelling and recovery was found to affect the surface roughness in single-point diamond turning. It is interesting to note that the effect of materials swelling for ductile materials would be overwhelmed by the impact of recovery when the depth of cut is extremely small and the front clearance is small. In addition, radically different surface roughness profiles were found for different materials even though they are machined under the same cutting conditions. The difference in the machining behaviour could not be accounted by the elastic recovery alone but by the plastic deformation induced in the machined layer. The findings in the present study provide an important means for improving the surface roughness in ultra-precision machining.     

Feed-forward control of fast tool servo for real-time correction of spindle error in diamond turning of flat surfaces

A fast tool servo is designed and tested to obtain sub-micrometre form accuracy in diamond turning of flat surfaces. The thermal growth spindle error is compensated for real time using a fast tool servo driven by a piezoelectric actuator along with a capacitive displacement sensor. To overcome the inherent non-linearity of the piezoelectric actuator, Proportional Integral (PI) feedback control with a notch filter is implemented. Besides, feed-forward control based on a simple feed-forward predictor is added to achieve better tracking performance. Actual machining data are discussed in detail to prove that the proposed fast tool servo is capable of fabricating flat aluminum specimens of 100 mm in diameter to a form accuracy of 0.10 μm in peak-to-valley error value.     

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.     

A novel method for determination of the subsurface damage depth in diamond turning of brittle materials

Micro-structured surfaces on brittle materials, e.g. ceramic and glass, are gaining increasing industrial applications such as optics, semiconductor and biomedical. However, these materials tend to be damaged with brittle fracture in machining. To generate crack-free surfaces, ductile-regime machining should be maintained for the entire micro-structured surface. In ductile-regime machining the material is removed by both plastic deformation and brittle fracture, but the cracks produced are prevented from extending into the finished surface. In this paper, a machining model has been developed for fast tool servo (FTS) diamond turning of micro-structured surfaces on brittle materials. Based on the model, a damaged region analysis method (DRAM) is proposed to determine the subsurface damage depth (C_m) by analyzing the surface damaged region of a machined micro-structured surface with sinusoidal wave along radial direction. Only one micro-structured surface is required to be machined to obtain C_m, which greatly reduces the effort for determination of C_m. With C_m, the maximum feedrate for machining a crack-free micro-structured surface can be determined. Machining experiments have verified the validity of DRAM.     

Orientation changes of aluminium single crystals in ultra-precision diamond turning

In this paper, the effects of cutting speed on the variation of surface texture and lattice rotation of diamond-turned surfaces were investigated. The {1 1 1} pole figures were determined at various locations by the X-ray diffraction method. The local lattice rotation at various locations on a machined groove by the electron back-scatter diffraction (EBSD) method was also obtained. A simulation of the orientation change was performed and the theoretical prediction was compared with the experimental results.     

Predictive modeling of surface roughness in grinding

The surface roughness is a variable often used to describe the quality of ground surfaces as well as to evaluate the competitiveness of the overall grinding system. This paper presents the prediction of the arithmetic mean surface roughness based on a probabilistic undeformed chip thickness model. The model expresses the ground finish as a function of the wheel microstructure, the process kinematic conditions, and the material properties. The analysis includes a geometrical analysis of the grooves left on the surface by ideal conic grains. The material properties and the wheel microstructure are considered in the surface roughness prediction through the chip thickness model. A simple expression that relates the surface roughness with the chip thickness was found, which was verified using experimental data from cylindrical grinding.     

A theoretical and experimental investigation into multimode tool vibration with surface generation in ultra-precision diamond turning

In ultra-precision diamond turning (UPDT), tool's high frequency vibration is natural mechanism influencing nanometric surface roughness of machined components. Its first mode high frequency vibration has been overemphasized. However, its multimode high frequency vibration (MHFTV) has not been reported. In the paper, the MHFTV and its effects on surface generation in UPDT are firstly studied. The experimental and theoretical results verify that (i) diamond tool naturally possesses multimode high frequencies, i.e. one sub-high frequency (SHF) for the tool shank tip, one high frequency (HF) for the tool tip, and one ultrahigh frequency (UHF) for the diamond tip; (ii) dampers cause the variation of tool's multimode high frequencies, under which the MHFTV together produces non-uniform zebra-stripe-like patterns at a machined surface; and (iii) cutting force has a linear relationship with and tool's stiffness has a reverse proportion to the amplitude of the MHFTV to influence surface generation, which can be used to improve surface quality.     

Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations

Due to the complexity of the machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true due to the demand of high-speed machining to increase productivity. In order to model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural–fuzzy approach appears to be ideally suited for this purpose. In this paper, the recently developed fuzzy adaptive network (FAN) is used to model surface roughness in turning operations. The FAN network has both the learning ability of neural network and linguistic representation of complex, not well-understood, vague phenomenon. Furthermore, it can continuously improve the initially obtained rough model based on the daily operating data. To illustrate this approach, a model representing the influences of machining parameters on surface roughness is established and then the model is verified by the use of the results of pilot experiments. Finally, a comparison with the results based on statistical regression is provided.     

FEM optimization of tool geometry based on the machined near surface''s residual stresses generated in diamond turning

In this work, based on the updated Lagrangian formulation and the commercial available software, Marc2001, a coupled thermo-mechanical plane-strain large deformation orthogonal cutting FE model is presented to simulate the diamond turning process and predict the residual stresses on the machined surface of workpiece. In order to consider the interactive influences of cutting edge radius, cutting velocity, rake angle and clearance angle on residual stresses, all simulations are programmed by an orthogonal design method, i.e. the combination design of general rotary method. As expected, two regression equations of tensile and compressive residual stresses are deduced according to the simulated results. The measured results in diamond turning show that the predicted results have a good consistency with the experimental ones. Therefore, some related analyses are carried out for the influencing factors based on the regression equations. Finally, the optimal analyses indicate that a rake angle of 15° and a clearance angle of 10° are the optimum geometry of a diamond tool in turning of ductile materials when this tool has a cutting edge radius of 100–300 nm.     

A power spectrum analysis of effect of rolling texture on cutting forces in single-point diamond turning

In most of the existing metal cutting theories, the workpiece is assumed to be homogeneous and most continuum theories do not take into account the effect of crystallographic anisotropy that causes variations in the shear plane at the grain level and hence of the cutting force. As the depth of cut in single-point diamond turning (SPDT) is usually less than the average grain size of a polycrystalline aggregate, cutting is generally performed within a grain. At this scale, the difference in the individual grain properties cannot be integrated out and a continuum solution would be insufficient. As a result, this paper presents a power spectrum analysis of the periodic fluctuation of micro-cutting forces in SPDT of polycrystalline materials. The experimental results show that the features of the power spectra of the cutting forces can be well correlated with the change of rolling texture of the materials being cut. These findings help to explain quantitatively the fluctuation of micro-cutting forces and hence the effect of rolling texture in SPDT, which are not encountered in conventional machining.     

Effect of tool nose radius and tool wear on residual stress distribution in hard turning of bearing steel

This study presents a experimental investigation to clarify the effects of tool nose radius and tool wear on residual stress distribution in hard turning of bearing steel JIS SUJ2. Three types of CBN tools with different nose radius (0.4, 0.8 and 1.2 mm) were used in this study. The residual stresses beneath the machined surface were measured using X-ray diffraction technique and electro-polishing technique. The results obtained in this study show that the tool nose radius affects the residual stress distribution significantly. Especially the effect on the residual stresses at the machined surface at early stage of cutting process is remarkable. For the tool wear, as the tool wear increases, the residual stress at the machined surface shifts to tensile stress range and the residual compressive stress beneath the machined surface increases greatly.     

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.