Ultra-precision Machining Process Research Articles

Fabrication and service of all-ceramic ball bearings for extreme conditions applications

Hot isostatic pressing silicon nitride material has properties that most metal materials do not have, such as low specific gravity, high strength, high stiffness, wear resistance, corrosion resistance, extreme temperature resistance, electrical insulation, no magnetic permeability, and excellent dimensional stability Performance, self-lubricating performance, etc. It is one of the ideal alternative materials for the manufacturing of bearings applied to various extreme conditions. This manuscript focuses on the practical needs of bearings for environmental equipment such as extreme temperature and marine corrosion. These bearings are used to improve the ultimate speed and load capacity of the whole steel bearing design system in ultra-high speed applications (such as machine tool spindle and gas turbine engine); to eliminate corrosion and reduce friction under extreme temperature or corrosion conditions, so as to improve system performance. In this paper, from the preparation of ceramic bearing materials to the ultra-precision machining process of ceramic bearing components, the development status of ceramic bearings in recent years is introduced, and the future development and application prospect of ceramic bearings are prospected.

Multi-Physics Fields Based Nonlinear Dynamic Behavior Analysis of Air Bearing Motorized Spindle.

The air bearing motorized spindle (ABMS) is the key component of the ultra-precision machine tool, which plays an important role in the ultra-precision machining process and directly influences machining accuracy. The influence of unbalanced magnetic force (UMF) on the nonlinear dynamic behavior of the ABMS is not understood clearly. To reveal the potential influence of the UMF, a mathematical model of the ABMS considering multiphysics fields is established. The variation trend of the UMF is simulated, and the nonlinear dynamic behavior of the ABMS is analyzed which emphasizes on the stability of the rotating shaft. It is shown that the UMF varies linearly at large rotor eccentricity which meets well with previous research, but it is noteworthy the UMF varies nearly to a quadratic function at small rotor eccentricity. The result of rotor dynamics shows that the UMF can change the converge position of the rotor center and the converge speed. Moreover, when at certain rotor mass and external load, the UMF can enlarge the stability boundary of the rotor. This research provides an example of analyzing the nonlinear dynamic behavior of the ABMS considering multiphysics fields which may help to the further investigation.

Mechanism of Controllable Force Generated by Coupling Inverse Effect of Piezoelectricity and Magnetostriction

A method based on piezoelectric and magnetostrictive coupling inverse effect to generate precise controllable force is proposed to meet the requirement of manipulation force control in ultra-precision machining and assembly process. According to the principle of magnetic flux continuity, combine with the characteristics of piezoelectric and magnetostrictive inverse effects, the working mechanism of force generation is analyzed, and the theoretical model of the relationship between output force and parameters which include material characteristics, geometric parameters, working voltage of piezoelectric ceramics is established. An experimental device consisting of piezoelectric ceramic driving power supply, strain gauge, static strain tester, micro laser displacement sensor, force sensor, data acquisition card and magnetic force control component is developed. The relationship between output magnetic force and air gap or working voltage are studied by experiment and simulation. The results show that the output force variations of simulation and experiment are close. The output magnetic force fluctuation is small and with good stability. It verifies the consistency and correctness of the theoretical, simulation and experimental results.

Recent advances in ultraprecision abrasive machining processes

Traditional approaches to understanding ultraprecision machining processes such as grinding, polishing, lapping, micromachining, machining, etc., have focused on developing analytical, semi-empirical and empirical models that seek to explain the output of processes based on many input variables. However, those models are not very well suited to providing inputs to develop improved abrasive products such as grinding wheels, lapping wheels, honing laps, coated abrasives, loose abrasives and their associated bonding systems and lubricants. In order to develop new products to improve ultraprecision processing of materials, it is necessary to focus on the mechanisms of microscopic interactions between abrasive products and the workpiece material. This paper reviews the current grinding theories and the methods employed to understand microscopic interactions due to cutting, plowing and sliding motions and how they can be used to develop new products using materials science principles that enhance and uniquely describe the removal of material in ultraprecision machining processes.

Molecular dynamics study on deformation behaviour of monocrystalline GaN during nano abrasive machining

Molecular dynamics simulations are carried out to investigate the nano abrasive machining of monocrystalline gallium nitride (GaN). Effects of the cutting velocity, depth of cut (DOC) and abrasive shape on the atomic strain, stress, temperature, cutting forces, and deformation layer are systematically investigated, aiming at understanding the deformation behaviour of monocrystalline GaN during nano abrasive machining. The results show that the strain, stress and temperature were increased by using the higher cutting velocity, the larger DOC or cub-octahedral abrasive. Being affected by both the average stress and the elasto-plastic deformation zone right ahead the diamond particle, the cutting forces increase with the increase in DOC but decrease under a larger cutting velocity, or when using a cub-octahedral abrasive. The deformation layer in the subsurface is insensitive to the cutting velocity, while impressively shrinks under a larger DOC or cub-octahedral abrasive used. As the stress and temperature rise, the use of higher cutting velocity, larger DOC or cub-octahedral abrasive would facilitate the nucleation of dislocation, phase transition and the development of pile-up. This work can enrich the understanding on the nanoscale deformation mechanism of monocrystalline GaN material during the ultra-precision machining process.

Enhancing Ductile-mode Cutting of Calcium Fluoride Single Crystals with Solidified Coating

Positive improvements have been observed during machining brittle materials under high hydrostatic pressure, but the techniques to achieve such desirable effects often utilize complex and expensive equipment or tools. This work presents a cost-efficient method to achieve ductile-mode machining of brittle materials at higher uncut chip thicknesses, by the application of a solidified coating on workpiece surface before a machining process. Orthogonal microcutting experiments were conducted on calcium fluoride single crystals oriented with the (111) plane and an increase in critical uncut chip thickness was observed with the solidified coating. The primary cause has been resolved to be mechanical-related and results in a stabilized microcutting process. Transmission electron microscopy provided evidence of slip deformation occurring in the machined subsurface regions and a layer thickness of subsurface damages reduced by ~ 45% under the influence of the solidified coating. In addition, erratic fluctuations in direction of the resultant machining force were subdued with the applied coating, which is proved to be caused by the compressive stresses induced from the sandwiching of the CaF2 material between the tool and the solidified coating. The proposed technique successfully reduces the cost and pollution in the fabrication process of optical components from the use of coolant in an ultraprecision machining process to the time consumed by eliminating the subsurface damage with abrasive slurries in post-machining polishing.

Effects of AFM tip wear on evaluating the surface quality machined by ultra-precision machining process

In this paper, the influences of tip wear of atomic force microscope (AFM) on evaluating the surface quality were studied. Three typical ultra-precision machined surfaces respectively machined by ultra-precision grinding, ultra-precision turning, and ultra-precision polishing were chosen, and the silicon tips with different wear degrees, the new tip, the moderately worn tip, and the badly worn tip, were employed to scan these three surfaces. By analyzing the AFM scanning results from different tips, each type of surface was characterized with the methods of 3D surface texture parameters and power spectral density (PSD). It was found that the tip wear would mainly degrade the ability of tip on measuring the valley structure and cause more artifacts when measuring the peak structure, which resulted in the effects on evaluating surface roughness parameters and identifying the high-frequency harmonic components. Moreover, due to the different topography characteristics of these three ultra-precision machined surfaces, the influences caused by tip wear on the evaluation of the surface quality were reflected in different aspects.

On-machine surface measurement and applications for ultra-precision machining: a state-of-the-art review

Surface measurement is essential to enhance accuracy and efficiency in ultra-precision machining. In order to increase the measurement availability and efficiency, offline lab-based solutions are shifting towards the use of surface metrology upon manufacturing platforms. With the lack of remounting errors, on-machine surface measurement (OMSM) allows the deterministic assessment of manufactured surfaces just-in-time and also provides valuable feedback to the process control of ultra-precision machining. This paper is aimed at reviewing the state-of-the-art OMSM and applications in the ultra-precision machining process. The benefits and considerations on the integration of metrology are discussed. The merits and limitations among different OMSM types are compared as well. Finally, the challenges and outlook of the ultra-precision machining-metrology integration are highlighted.

Multimodal Data Fusion Using Multivariate Empirical Mode Decomposition for Automatic Process Monitoring

The recent leap forward in wireless sensing and communication technologies has brought forward the proliferation of multimodal sensing data and offered a unique viewpoint to study numerous complex systems and processes. Indeed, the mining of such sensing data is poised to promote the paradigm-shift from experience-based to evidence-driven process monitoring, control, prognostics, and optimization. Notably, an integration and effective fusion of such multimodal data has been an impending obstacle to utterly marshal their prowess. Despite the extensive attempt in the literature, multimodal data fusion is still in the embryonic stage, particularly considering the inherent nonlinear, nonstationary, and heterogeneous nature of the sensing data. In this article, we report a novel approach to fuse multimodal data from different channels via nonparametric multivariate empirical mode decomposition (EMD). The EMD decomposes each signal into a series of oscillatory modes called the intrinsic mode functions (IMFs) with a progressively lower frequency. The multivariate EMD guarantees that signals from different channels have the same number of components and are mode aligned. Capitalizing on the recurrence quantification analysis of the intrinsic state space reconstructed from the IMFs, we build a control chart to monitor process dynamics. Applications in ultraprecision machining processes suggest the effectiveness of the proposed algorithm.

Development and Application of Interferometric On-Machine Surface Measurement for Ultraprecision Turning Process

The continuing evolution of ultraprecision machining places an increasing need to perform surface measurement in the manufacturing environment. Development of on-machine surface measurement (OMSM) tools for ultraprecision machining processes will enable the reduction of measurement cycle time as well as the potential improvement of machining accuracy. In the present study, an in-house designed interferometer probe is integrated onto an ultraprecision diamond turning machine. System configuration, calibration scheme and various scanning strategies are first presented. The benefit of OMSM preserves the consistency between the machining and measurement coordinate system. Two applications of OMSM for ultraprecision turning process are further investigated. To further improve the surface accuracy, corrective machining is carried out based on the on-machine measured data. The profile accuracy of a cosine curve sample was improved after corrective machining with OMSM. Moreover, process investigation with OMSM was employed to model the effect of process parameters on the form error in ultraprecision cylindrical turning process. OMSM enables the consistent measurement of part coordinates for each experimental run, which is critical for acquiring a deterministic response for empirical modeling. A reduced quadratic model was built by means of response surface methodology and verified by the test for significance of the regression model. The confirmation tests show that the model predicted value conformed to the experimental value with a difference less than 4%.

Analysis of the influence of installation tilt error on the tool setting accuracy by laser diffraction.

In the ultra-precision machining process, it is important to detect the tool-workpiece distance by the laser diffraction effect. However, there is no absolute ideal situation for the tool setting of laser diffraction. It is necessary to consider the influence of installation tilt error on the tool setting accuracy and its compensation. In this paper, referring to the ideal optical axis, the influences of the incident laser tilt, CCD tilt, and rectangular orifice tilt on the peak position of the diffraction fringes in the CCD phase are modeled and analyzed to determine the relative effects on the tool setting accuracy for tool-workpiece distance detection. The tilt angle of the incident laser is measured by extracting the CCD pixel position, where the central peak point is located. The CCD tilt angle is detected by extracting the CCD pixel positions, where the first-degree peak points are located. The inclination direction and the inclination angle of the rectangular orifice are detected by extracting the bending direction and the bending degree of the fringes in the horizontal direction, and the error compensation is performed according to the inclination angle. This study establishes a compensation method for installing tilt error, and the optimized installation process parameters can be acquired under certain experimental conditions according to the experimental data to ensure the results' accuracy.

A generalized dynamic model for spindle vibration influencing surface topography in different ultra-precision machining processes

Ultra-precision machining (UPM) typically involves ultra-precision diamond turning (UPDT), ultra-precision raster milling (UPRM), and ultra-precision grinding (UPG). In UPM, spindle vibration (SV) is a natural feature majorly influencing surface topography. In this paper, a dynamic model for SV was generalized to study its distinctive effects on surface topography in different UPM processes. The theoretical results were identified well by a series of cutting tests. In UPDT, constant cutting forces induce harmonic SV to produce regular patterns. In UPRM, periodical impulsive cutting forces cause periodical impulsive SV to generate quasi-regular patterns. In UPG, random impulsive cutting forces result in partially random impulsive SV to form partially random patterns. The generalized model can be employed to predict the effects of SV on surface generation in UPM.

Numerical analysis and experimental research on the angular stiffness of aerostatic bearings

Abstract The machined surface topography in the ultra-precision machining process was obviously affected by the angular stiffness of aerostatic bearings. In this study, a numerical model was established to investigate the influence of operating conditions, geometric parameters and manufacturing error on the angular stiffness of aerostatic bearings with orifice restrictor. The calculation procedure for bearing angular stiffness was proposed based on the finite element method (FEM) and the proportional division method. The numerical results presented that film pressure distribution was significantly affected by the bearing deflection angle and the manufacturing error. It was confirmed that there was a suitable film thickness corresponding to the maximum angular stiffness, and the suitable film thickness increased with the growth of orifice diameter. The bearing angular stiffness increased with the rise of eccentricity, the thrust bearing angular stiffness can be improved by increasing the amplitude of non-flatness error and the thrust eccentricity, which can be used to improve the machining quality of ultra-precision machine tools. Besides, a precision experimental system was constructed to measure the angular stiffness of aerostatic bearings at the different supply pressure. The biggest difference between the experimental data and calculation results was less than 6.7%, which demonstrated the numerical calculation method proposed in this paper can be applied to optimize the angular stiffness of aerostatic bearings.

Surface damage mechanism of monocrystalline silicon during single point diamond grinding

Surface damage mechanism of single crystalline Si (100) under single point diamond grinding was investigated in the present study. The result, for the first time, showed that the ductile and brittle material removal appeared at different grinding positions of the diamond wheel due to the varied kinematics of the diamond grits in the cylindrical face and end face. Under the dynamic pressure of the diamond grits, amorphization and the transformation to high pressure phases (Si-III and Si-XI) of Si occurred, which were identified by both XRD and Raman spectroscopy. In addition, surface oxidation and chemical reaction between the Si, O, C and N atoms was analyzed by the XPS, and the new products of Si3N4 and graphite oxide (GO) are firstly proposed to be the surface damage of Si and the tool wear mechanism during the ultra-precision machining process.

Burr formation mechanism of ultraprecision cutting for microgrooves on nickel phosphide in consideration of the diamond tool edge radius

Single-point diamond cutting is an efficient method to generate the V-shape microgrooves, but the burr forms easily at the microgroove edge when cutting ductile material, especially at small (micron level) cutting depth, and the burr increases with the reduction in the cutting depth. In this paper, the effects of plastic side flow in micro cutting are taken into account to explain the formation of burrs in ultraprecision machining process. The edge radius of diamond tool is measured by scanning probe microscope (SPM), and the mechanism of the burr formation is revealed with considering the edge radius of diamond tool and the cutting depth in machining nickel phosphide (Ni-P). In this way, an approach to restrain the burr formation is established so as to generate fine microgrooves.

Modelling of flow stress by correlating the material grain size and chip thickness in ultra-precision machining

Abstract Inducing compressive stress on the machined surface is a desirable practice in ultra-precision metal cutting to improve the part quality. An important parameter to analyse the machining performance is the material flow stress, which plays a crucial role in the material deformation characteristics in machining. As the dimensions of the workpiece descend from macro to micro scale in metal forming, the flow stress reduces accordingly. Hence, based on the ‘surface model’ analogy developed for metal forming coupled with the crystal plasticity effect, an attempt has been made in this study to construct a flow stress model for ultra-precision machining process. While developing the model, for the first time, the size factor (η, d/ho) is introduced to incorporate the material ‘grain size effect’ in ultra-precision machining. The proposed model is validated with experimental results of Al6082 alloy of different grain sizes. Orthogonal turning experiments were conducted on an ultra-precision machine by utilizing the concept of ‘cutting edge radius effect’, which is identified as the relative tool sharpness (RTS) and quantified as the ratio of undeformed chip thickness (hc) to edge radius (rn). In this paper, the investigation on the material flow stress is carried out by considering the phenomenon of the shifting material flow separation (cutting) from primary deformation zone to material deformation (ploughing and rubbing) at tertiary deformation zone. The distribution of contact stresses along the tool rake and flank faces at the minimum value of RTS (hc/rn) of 0.01 substantiates the ploughing effect (compressive stresses are induced into the machined layer) rather than chip separation. Moreover, the distinct variation of the machined surface quality and μ-chip morphology at the extreme low and high RTS conditions distinguishes the material ploughing effect from the cutting effect. Additionally, for the same RTS value, it is found that different grain materials (Cu and Mg alloy) exhibited variations in flow stress, chip morphology and surface quality. Therefore, material grain size is an influential factor for analysing machining performance with material flow stress at ultra-precision level.

Micro-optical fabrication by ultraprecision diamond machining and precision molding

Ultraprecision diamond machining and high volume molding for affordable high precision high performance optical elements are becoming a viable process in optical industry for low cost high quality microoptical component manufacturing. In this process, first high precision microoptical molds are fabricated using ultraprecision single point diamond machining followed by high volume production methods such as compression or injection molding. In the last two decades, there have been steady improvements in ultraprecision machine design and performance, particularly with the introduction of both slow tool and fast tool servo. Today optical molds, including freeform surfaces and microlens arrays, are routinely diamond machined to final finish without post machining polishing. For consumers, compression molding or injection molding provide efficient and high quality optics at extremely low cost. In this paper, first ultraprecision machine design and machining processes such as slow tool and fast too servo are described then both compression molding and injection molding of polymer optics are discussed. To implement precision optical manufacturing by molding, numerical modeling can be included in the future as a critical part of the manufacturing process to ensure high product quality.

Numerical optimization platform for precision glass molding by the simplex algorithm.

Precision glass molding (PGM) can fabricate aspherical lens and irregular optical products in a single step, but its applicability is currently limited by the thermally induced residual stresses and lens shape derivation after molding. To remove this barrier, this paper develops a numerical optimization platform for PGM based on a simplex algorithm and finite element simulation. It was found that the platform can effectively reduce the residual stress in a molded lens through cooling process optimization and minimize the lens shape derivation by die shape compensation. The platform established can improve the lens quality by PMG and make molded lenses have better quality than those manufactured by ultraprecision machining processes.

Heterogeneous recurrence monitoring of dynamic transients in ultraprecision machining processes

In situ monitoring and control of process variations are important for quality assurance in ultraprecision machining (UPM) processes. Recent advancements in sensing and communication technology have fueled increasing interests to develop sensor-based monitoring approaches for anomaly detection in the UPM process. However, conventional approaches are limited in their ability to address the complex dynamics hidden in the nonlinear and nonstationary processes. As a result, it is difficult for them to effectively capture the process variations of UPM. This paper presents a new heterogeneous recurrence monitoring approach to detect dynamic transients in UPM processes. First, a high-dimensional state space is reconstructed from in situ sensing signals. A Dirichlet process (DP) driven clustering approach is then developed to automatically segment the state space into local recurrence regions. Furthermore, a fractal representation is designed to characterize state transitions among recurrence regions and extract novel measures to quantify heterogeneous recurrence patterns. Finally, we integrate a multivariate control chart with heterogeneous recurrence features for in situ monitoring and predictive control of the UPM process. Experimental results showed that the proposed approach effectively detects transitions with a small magnitude, i.e., ρ=28 to ρ=27 in the Lorenz system, and identifies the shift from stable cutting (Ra=35nm) to unstable cutting (Ra=82nm) in UPM processes with an average run length of 1.0. This paper presents a novel data-driven DP clustering approach to characterize heterogeneous recurrence variations and link with the quality of surface finishes in UPM processes. This new DP recurrence approach circumvents the need to empirically define local recurrence regions and is shown to have strong potentials for manufacturing process monitoring and control that will increase the surface integrity and reduce rework rates.

Heterogeneous Sensor Data Fusion Approach for Real-time Monitoring in Ultraprecision Machining (UPM) Process Using Non-Parametric Bayesian Clustering and Evidence Theory

The aim of this paper is to detect the incipient anomalies in a ultraprecision machining (UPM) process by integrating multiple in situ sensor signals. To realize this aim we forward a Bayesian non-parametric Dirichlet Process (DP) decision-making approach for real-time monitoring of UPM process using the data gathered from multiple, heterogeneous sensors. The sensor signals are acquired under different experimental conditions from a UPM setup instrumented with a heterogeneous sensing array consisting of miniature tri-axis force, tri-axis vibration, and acoustic emission (AE) sensors mounted in close proximity to the cutting tool. We track the prominent nonlinear and non-Gaussian signal patterns evident in the experimentally acquired sensor data using an adaptive non-parametric DP modeling technique. A cohesive decision concerning the UPM process condition is made by developing a new supervised learning method, which integrates the DP-model state estimates with an evidence theoretic sensor data fusion method. Using this combined DP-evidence theoretic approach, UPM process drifts and anomalies, such as sudden changes in the depth of cut, feed rate, and spindle speed that deleteriously affect surface finish, and hence cause high yield losses, are detected and classified with over 90% accuracy (with ${ standard deviation). We compared these results with popular classification techniques, e.g., naive Bayes, self-organizing map, and support vector machine; these conventional techniques had classification accuracy in the range of 83%–88%. Consequently, this research makes the following practically relevant contributions: 1) real-time identification of the incipient UPM process anomalies from multiple sensors and 2) prescribing the optimal subset of sensors signals contingent to particular process anomalies.