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.     

A theoretical and experimental investigation into five-DOF dynamic characteristics of an aerostatic bearing spindle in ultra-precision diamond turning

In ultra-precision diamond turning (UPDT), spindle vibration has great influence on machining precision of high precision optical components. However, the spindle-vibration mechanism has not been fully understood. In this study, mathematical solutions for a proposed five-degree-of-freedom (FDOF) dynamic model of an aerostatic bearing spindle are derived to explore natural mechanisms of spindle vibration. Thus, the potential benefits of the solutions are to be applied for the prediction and optimization of the effects of spindle vibration on surface generation. Its dynamic characteristics possess three translational frequencies along the radial and axial directions, a spindle rotational frequency (SRF), and a pair of coupled tilting frequencies (CTFs) around the radial directions influenced the SRF. The theoretical results are identified by the frequency characteristics of thrust cutting forces, and the periodic, concentric, spiral, radial and two-fold patterns (PCSRPs) of the machined and simulated surface topographies, respectively.     

A theoretical and experimental study of surface generation under spindle vibration in ultra-precision raster milling

In ultra-precision raster milling (UPRM), the impulse spindle vibration induced by the impulse-like cutting forces is intrinsic and special mechanism majorly influencing surface topography. It is fundamentally distinctive with the step spindle vibration induced by the step-like cutting forces in turning. However, no work has been conducted to study surface generation under the impulse spindle vibration in UPRM in depth. Consequently, this paper theoretically and experimentally elaborates that in UPRM, (i) the impulse spindle vibration includes the axial, radial and coupled-tilting spindle vibration with damping; (ii) the excitation frequency of the impulse-like cutting forces, i.e. spindle speed, determines the spindle vibration characteristics, i.e. synchronous or asynchronous spindle vibration; (iii) the coupled-tilting spindle vibration is a predominant factor influencing surface generation; and (iv) the irregular spindle-vibration waves induced by the impulse spindle vibration produce one of the irregular, lattice-like and stripe patterns or their hybrids at a milled surface.     

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.     

Dynamic modelling of shear band formation and tool-tip vibration in ultra-precision diamond turning

This paper proposes a dynamic model to correlate the two basic physical phenomena in ultra-precision diamond turning, i.e. the formation of adiabatic shear band (ASB) and high frequency tool-tip vibration (HFTTV). The conventional approach explains the former using a static model without consideration of the latter. In this paper, a dynamic model is developed to reflect how the ASB and the HFTTV interactively affect each other. To illustrate the validity of this model, a novel experimental method is proposed and the effect of HFTTV on cutting force, surface roughness and chip morphology of ASBs is discussed in terms of the variation of strain rates.     

The effects of spindle vibration on surface generation in ultra-precision raster milling

Spindle vibration has a significant influence on surface quality of ultra-precision-machined components. However, relatively few studies on the particular spindle vibration under the excitation of intermittent cutting forces in ultra-precision raster milling (UPRM) have been reported. In this study, a specialized model for an aerostatic bearing spindle under the impulsive excitation from intermittent cutting forces of UPRM is developed and its derived mathematical solutions reveal that the spindle vibration is impulsive response. The theoretical and experimental results signify that the impulsive spindle vibration produces inhomogeneous scallops forming ribbon-stripe patterns and irregular patterns like run-out on a surface of UPRM. The potential benefits for UPRM are the theoretical supports for optimization and prediction of surface generation through the optimal selection of spindle speed.     

A review of machine-tool vibration and its influence upon surface generation in ultra-precision machining

Vibration in ultra-precision machining (UPM) is an intrinsic physical phenomenon, which is a key factor influencing surface generation. With a focus on passive vibration, this paper reviews the latest research into vibration characteristics and the effect of vibration on surface generation in UPM. The opportunities and challenges facing researchers are also discussed and suggestions are made for future related studies. It is found that active vibration can possibly be employed to improve surface quality influenced by passive vibration in UPM.     

Theoretical and experimental analysis of nano-surface generation in ultra-precision raster milling

The fabrication of high-quality freeform surfaces is based on ultra-precision raster milling, which allows direct machining of the freeform surfaces with sub-micrometric form accuracy and nanometric surface finish. Ultra-precision raster milling is an emerging manufacturing technology for the fabrication of high-precision and high-quality components with a surface roughness of less than 10 nm and a form error of less than 0.2 μm without the need for any additional post-processing. Moreover, the quality of a raster milled surface is based on a proper selection of cutting conditions and cutting strategies.Due to different cutting mechanics, the process factors affecting the surface quality are more complicated, as compared with ultra-precision diamond turning and conventional milling, such as swing distance and step distance. This paper presents a theoretical and experimental analysis of nano-surface generation in ultra-precision raster milling. Theoretical models for the prediction of surface roughness are built. An optimization system is established based on the theoretical models for the optimization of cutting conditions and cutting strategy in ultra-precision raster milling. A series of experiments have conducted and the results show that the theoretical models predict well the trend of the variation of surface roughness under different cutting conditions and cutting strategies.     

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.     

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.     

A theoretical and experimental investigation of the tool-tip vibration and its influence upon surface generation in single-point diamond turning

This paper presents a theoretical and experimental investigation of the influence of tool-tip vibration on surface generation in single point diamond turning (SPDT). Although it is well known that the relative vibration between the tool and the workpiece plays an important role in the surface generation in single-point diamond turning, most of the prior work has been focused on studying the relative tool-work vibration in the infeed (thrust force) direction while the significant contribution of the effect of the tool-tip vibration in the cutting force direction has been overlooked. In the present study, two characteristic peaks (twin peaks) are identified and found to be corresponding to the tool-tip vibrations by power spectrum density (PSD) analyses. The vibrations possess the features of small amplitude but high frequency. A physical model is proposed to capture the dominant factor based on the characteristic and it reveals that the twin peaks are attributed by the impact between the tool tip and workpiece and the process damping effect. Hence, a geometric model of surface roughness is proposed to take account of tool-tip vibration and it is verified through a series of experiments. The simulation results have been found to agree well with the experimental results.     

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.     

A comparison of dry and air-cooled turning of grey cast iron with mixed oxide ceramic tool

The present work compares the performance of a mixed oxide ceramic tool in dry and air-cooled turning of grey cast iron. First, the study was done in the range of process parameters where dry turning provided satisfactory performance. The contours of surface roughness and tool life were generated with the help of trained neural networks. A novel procedure of neural network training is used in this work. The study was extended to the range in which dry turning performed poorly in terms of tool life. Tool wear, surface roughness of the machined job and forces and vibration during the cutting were studied. It was observed that air-cooling significantly reduces the tool wear at high cutting speed. At higher cutting speeds, where the dry turning performs very poorly, the air-cooled turning provides an improved surface finish also apart from the reduction in tool wear. In all the cases, the cutting and feed forces get reduced in air-cooling. Thus, air-cooled turning of grey cast iron with mixed oxide ceramic tools offers a promising environment-friendly option.     

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.     

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.