Ultra Precision Research Articles

Calculation of Tool Offset and Tool Radius Errors Based on On-Machine Measurement and Least Squares Method in Ultra-Precision Diamond Turning

Metal mirrors will be widely used in the coming decades. Therefore, as one of the enabling technologies for metal optical freeform surface manufacturing, ultra-precision (UP) diamond turning error compensation has become a research hotspot. However, for the tool offset error and tool radius error, which are the main errors in UP diamond turning, no precise and efficient calculation method has been found in the literature. In this study, a more precise and efficient algorithm was developed and validated in three ways using on-machine measurement data and profilometer measurement data. After one compensation, the tool offset error can be reduced to below 0.1 μm, and the tool radius error can be reduced to below 1 micrometer, which will significantly improve the UP turning accuracy and efficiency of optical parts.

Molecular dynamics simulation of the influence of nanocutting parameters on microstructure of AISI M2

Molecular dynamics simulation has become the main analysis method of ultra precision machining of various materials. In this research, molecular dynamics method was used to explore the influence of nanocutting parameters on amorphous atoms, atomic coordination numbers, atomic strain and dislocations of AISI M2 workpiece. LAMMPS was used to construct the molecular dynamics model for CBN tool cutting AISI M2. The polycrystalline model of the workpiece contained 12 grains and iron, chromium and tungsten atoms. The polycrystalline model of the tool contained 3 grains and boron and nitrogen atoms. Tersoff, EAM, Morse and L-J potential energy functions were used to characterize the interaction between atoms. The following results were obtained through 8 groups of simulation experiments: (1) Both cutting speed and cutting depth promoted the amorphous transformation of workpiece atoms. (2) Under the extrusion of the tool, atoms with high coordination numbers were produced in the contact area between the tool and the workpiece. (3) The cutting depth was positively correlated with the average strain of workpiece atoms. Large strain atoms mainly occurred in the cutting area and gradually extended into the workpiece. (4) 1/2 < 111> dislocation was the most common dislocation form in nanocutting. This research plays a rich role in molecular dynamics simulation of nanocutting polycrystalline alloys.

INTELLIGENT MONITORING SYSTEM FOR REAL-TIME OPTIMIZATION OF ULTRA-PRECISION MANUFACTURING PROCESSES

In the realm of ultra-precision manufacturing, the minutiae of process control and material handling are paramount to achieving the highest levels of product quality and manufacturing efficiency. The industry faces a significant challenge: maintaining and enhancing the precision of manufacturing processes in real-time to ensure optimal output quality while minimizing waste and energy consumption. This challenge is compounded by the increasing complexity of products and the materials used, requiring ever more precise and adaptive manufacturing techniques. The importance of addressing this challenge cannot be overstated, as it directly impacts the competitiveness, sustainability, and innovation capacity of manufacturing firms. The development of an intelligent monitoring system that integrates advanced precision metrology techniques presents a promising solution to this problem. Such a system would enable real-time optimization of manufacturing processes, leveraging cutting-edge technologies and data analytics to dynamically adjust parameters for optimal performance. By doing so, it would not only enhance the precision and efficiency of manufacturing operations but also contribute significantly to sustainable manufacturing practices by reducing waste and energy consumption. This concept paper proposes the development of this intelligent monitoring system, outlining its potential impact on the ultra-precision manufacturing industry.&#x0D; Keywords: Ultra Precision, Monitoring, Processing, Real Time.

Low-energy ion beam erosion of Si with simultaneous co-deposition of metallic surfactants: Experimental and simulated data

Ion beam erosion of Si under co-deposition circumstances supports the formation of surface patterns on the nano- and micrometer scale. To evaluate the effect of surfactant sputtering within a setup relevant for ultra precision surface finishing, this work is presented. We present data for samples prepared with Ar ion beam erosion, at low ion energy. Al, Cu, steel, Cr, Ni, Mo, Ti, Ta, Zn and Si were chosen as co-deposition material. Simultaneous irradiation of the co-deposition material and the Si samples were performed with a broad beam ion source. The structuring and pattern formation are discussed with SEM and AFM measurements. It was shown that the evolution of structures on the substrate is induced by the silicide-forming metals. This corresponds with a higher surface roughness. Whereas the non-silicide-forming metals did not show patterning, and accordingly, lower surface roughness. Measurements regarding the Si removal rate showed, that it depends on the co-deposition material. Supporting simulation data proposed that the effect of the co-deposition material on the Si removal is determined by the combination of sputtering and scattering properties of the co-deposition material. The ratio of scattered Ar ions to sputtered metal particles describes the effect on the removal change. For metals which tend to higher scattering, the removal is enhanced. This applies for most of the metals with higher atomic number. Whereas the metals with lower atomic number favor self-sputtering, which results in an decreased Si removal.

Study on tool wear and optimization of machining parameters in laser-assisted fast tool servo machining of glass-ceramic

Glass-ceramic is difficult to be ultra precision machined due to its high hardness and brittleness. Laser-assisted fast tool servo machining (LAFTSM) of glass-ceramic optical free-form surface was carried out with tool wear as the characteristic value to study the machining quality of glass-ceramic. Orthogonal experiments on LAFTSM were conducted using the Taguchi method (TM). The range of tool wear reduction obtained by comparing laser-assisted machining (LAM) with fast tool servo (FTS) machining is 48.83%–64.12%. The order of contribution of each machining parameter obtained through variance analysis to the reduction of tool wear is: spindle speed &gt; laser power &gt; feed rate &gt; piezoelectric frequency. The optimal combination of machining parameters that can minimize tool wear obtained through signal-to-noise ratio (S/N) analysis is: spindle speed 55 rpm, feed rate 0.01 mm/rev, piezoelectric frequency 8 Hz, laser power 75 W. Artificial neural network (ANN) and genetic algorithm (GA) were used to fit and optimize the machining parameters and experimental results in TM orthogonal experiments. The fitting values of ANN are highly consistent with the orthogonal experimental results. The optimal combination of machining parameters obtained after GA optimization analysis is: spindle speed 50 rpm, feed rate 0.015 mm/rev, piezoelectric frequency 4 Hz, laser power 75 W. Experiments were conducted using the optimal combination of machining parameters of TM and ANN, the results showed that ANN performs better than TM in predicting minimum tool wear and optimizing machining parameters. This study provides a reference for LAFTSM and the research methods of tool wear.

Experimental investigation on cutting force and machining parameters optimization in in-situ laser-assisted machining of glass–ceramic

Glass-ceramic is a typical hard and brittle material that is difficult to use for ultra precision machining. In order to improve the machining quality of glass–ceramic, orthogonal experiments on in-situ laser-assisted machining (LAM) of glass–ceramic were carried out with cutting force as the characteristic value. The maximum reduction in the resultant force of cutting force in in-situ LAM was 56.13%. The contribution order of each machining parameter to reducing cutting force is: spindle speed > laser power > feed speed > cutting depth. Response surface methodology (RSM) was used to conduct experiments and establish a regression model for predicting cutting force. The influence law of four machining parameters on cutting force was studied through three-dimensional response surface. The optimal combination of machining parameters to minimize cutting force obtained through RSM optimization is: spindle speed 400.51 rpm, feed speed 0.03 mm/rev, cutting depth 18.91 μm, laser power 74.78 W. The RSM experiments were trained, predicted, and optimized using artificial neural network (ANN) and genetic algorithms (GA). The fitting values of the ANN model are highly consistent with the experimental values of RSM. The optimal machining parameter combination obtained through GA optimization is: spindle speed 400 rpm, feed speed 0.01 mm/rev, cutting depth 20 μm, laser power 75 W. Experiments were conducted using the optimal machining parameters of RSM and ANN respectively, and the results showed that ANN is more ideal for optimizing machining parameters and predicting minimum cutting force. This study provides guidance and reference for glass–ceramic in-situ LAM and parameter optimization method for cutting force.

Monitoring of machining process anomalies in diamond turning of Ti6Al4V alloy using transfer learning-based algorithms

In-process monitoring of anomalies in Ultra Precision Machining (UPM) can improve and ensure product quality and lower manufacturing costs, which is essentially important for industrial-scale ultraprecision manufacturing. UPM is found to be extremely sensitive towards minute instabilities; if such nascent anomalies are not detected can cause irrecoverable defects. However, the classification of the diamond-turning process through conventional monitoring techniques is challenging. This study explores the use of spectrogram-based deep learning to enable real-time, intelligent process monitoring in UPM. The vibrational signals obtained from machining are transformed into log-spectrogram images. These images obtained during machining allow the rendering of more accurate and richer features of signals, as most of the time domain signal obtained in UPM is susceptible to noise and exhibits several non-linearities. The current approach also uses Transfer Learning (TL) to address the feature selection problem. TL is adopted by using the deep learning (DL) models, which have already been developed for classifying different Images. DL pre-trained networks, including VGG19, ResNet50 and Densenet201, are studied for classifying the anomalies. These TL models are applied to the spectrogram images for the classification of normal and abnormal machining in UPM. Among the TL models, the VGG19 model yields the highest classification accuracy at 90%, which demonstrates the potential feasibility of the TL for monitoring process anomalies in UPM.

Analysis of the effect of tool geometry on the cutting process of polycrystalline Fe-Cr-W alloy based on molecular dynamics simulation

In order to study the influence of tool geometry on the machining mechanism of alloy tool steel in the process of ultra precision turning, the polycrystalline molecular dynamics model of alloy tool steel is established with Fe, Cr and W, and the molecular dynamics model of tool is established with B and N. Four potential energy functions, Tersoff, EAM, Morse and L-J, are used to characterize the interaction between atoms in the model. The effects of tool geometry on hydrostatic stress, cutting force, cutting temperature and amorphous atoms in the turning process are analyzed. Research indicates:(1) Hydrostatic stress is mainly concentrated in the contact position between the tool tip and the workpiece, and it is compressive stress; (2) Cutting forces fluctuate and are significantly affected by tool geometry; (3) The cutting heat of about 1000K is concentrated in the chip, and the tool clearance angle has a great influence on the cutting temperature. (4) Amorphous atoms are formed at the chip location and the machined surface, and eventually turn into chips and the metamorphic layer of the machined surface.

Reactive ion beam smoothing of rapidly solidified aluminum (RSA) 501 surfaces for potential visible and ultraviolet light applications

Optical elements made of aluminum with surface roughness in the sub-nanometer range are required for applications in the visible (VIS) and ultraviolet (UV) spectral range. Rapidly solidified aluminum (RSA) 501 is an interesting candidate to produce sufficiently smooth surfaces for these applications in an ultra-precision (UP) fly-cutting process. However, the polycrystalline grain structure and precipitates contained in the material limit the achievable surface roughness. In this research, a reactive ion beam finishing process of RSA 501 is investigated employing an electron cyclotron resonance (ECR)-driven ion source using CF4 and N2 gasses. Emphasis is placed on understanding the etching mechanisms that influence the topographic evolution to provide the basis for future production processes using the material for UV optics. Material composition characterization is applied to analyze the interaction between the reactive ion species and the RSA material. Surface modification transferring the native oxide top layer to an in situ forming and developing aluminum fluoride or -nitride etch front layer is found to prevent grain orientation-dependent etching. The effect of the ion incidence angle on the etch rates of precipitates and bulk material can be used to reduce the height of precipitates protruding from the surface after the UP-machining process. A surface roughness value of Sq = 0.9 nm ± 0.1 nm (areal root mean square height) is achieved in the micro-roughness range when etching at 40° and 80° angle of incidence using collimated ion beams with CF4 process gas.

Radial Error Motion Measurement and Its Uncertainty Estimation of Ultra Precision Axes of Rotation with Nanometer Level Precision.

The radial error is the key performance indicator of ultra-precision axis. In order to measure and evaluate the radial error of ultra-precision axis with nanometer accuracy, a measurement system with an accuracy of nanometer based on capacitive displacement probes and standard spheres is developed. The nonlinearity error of capacitive displacement probes, misalignment error of the probes, eccentric error of standard spheres, error caused by environment temperature change, environment vibration and error separation methods are analyzed and the effects of the above factors are obtained; Multiple measurement examples carried out with the measurement system this paaper constructed indicate the repeatability of the measurement system reaches 10.5 nm and the roundness error of artifact separated is less than 4.03 nm. In order to evaluate the measurement dispersion of the ultra-precision axis radial error, the major uncertainty components and the complete process of the comprehensive evaluation of the measurement uncertainty are proposed. The combined uncertainty of radial error motion measurement of the ultra-precision axis with Donaldson reversal is 31.64 nm (k = 2).

Research on the effect of cutting parameters on the machinability of polycrystalline Fe-Cr-W alloy by molecular dynamics simulation

Molecular dynamics simulation has become a major theoretical analysis method for ultra precision machining of various materials. Large Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is used to construct a molecular dynamics model for cutting polycrystalline Fe-Cr-W alloy with CBN tool. The geometric parameters of the tool model are: the rake angle is −10°, the clearance angle is 7°, and the tool tip radius is 1.5 nm, including 8570 atoms. The size of the workpiece model is 24 nm × 10 nm × 10 nm, including 203,893 atoms. Ovito is used to visually analyze the influence of cutting parameters on the machinability of workpieces. The results show that the extrusion of the tool on the workpiece makes the atoms of the workpiece move and become chips and machined surfaces. Excessive cutting speed and depth will produce large hydrostatic stress, large cutting force, high cutting temperature and deteriorate the machined surface.

Cost-effective fabrication of As40Se60 glass lenses enabled by SPS-SPDT process

In this paper, we prepare chalcogenide glass (ChG) discs with As40Se60 composition employing spark plasma sintering (SPS) with the advantage of higher raw materials utilization ratio compared with conventional coring and cutting processes. The hardness, composition, structure of the ChG discs are evaluated by HVS, EDS, XRD, Raman characterizations. The Vickers hardness of SPS glass (140.6 HV) is slightly lower than that of base glass. EDS data show that the atomic ratio of SPS glass does not deviate from the base glass. XRD and Raman results confirm that the SPS glass still retains the original amorphous structure. By ultra precision single point diamond turning (SPDT) method, an aspheric lens is fabricated from the SPS glass discs with the lens profile perfectly matched with the design. The modulation transfer function (MTF) of the aspheric lens within the full field of view is above 31%, which is comparable to base glass lenses and indicates lens performance satisfies the requirement of practical imaging devices.

Digital surface twin for ultra-precision high performance cutting

Increasing productivity of ultra-precision (UP) machining is vital to apply this technology in a broader range of applications. In order to achieve this goal, technologies such as diamond cutting with multiple cutting edges or the application of electromagnetic levitation guides are researched. Due to the additional, influencing factors from these technologies, a digital surface twin is beneficial for predicting surface features and characteristics. In this work, two approaches for generating a digital surface twin are investigated: a surface simulation based on numerical height maps and a dexel-based material removal simulation. Both incorporate multi degree of freedom position data provided by the levitation guide. Fly-cutting experiments are conducted to validate the digital twin approaches. Both approaches are able to predict surface profile, surface roughness and waviness with high accuracy. It is also shown, that the digital twin can support the development of compensation approaches for tool offsets. In conclusion digital surface twins for ultra-precision cutting offer a high potential to support productivity improvement especially in combination with axis position data. Further work will focus on real-time integration of the approaches.

Aerostatically sealed chamber as a robust aerostatic bearing

Aerostatic bearings are typically used in ultra precision and high speed applications in controlled environments. The present study expands this operating domain. The present study experimentally investigates the performance and feasibility of a novel design for a robust air bearing consisting of an aerostatically sealed pressurized volume. A suitable operating domain for the bearing system was characterized based on measurements of the load capacity, friction moment, chamber flow, and seal flow rate at various opposing surface run-outs and supply pressures. The highest measured load capacity was 18.86 kN at 0.330 mm run-out, and decreased to 12.22 kN load at 3.804 mm run-out. The study provided corroborative evidence on the feasibility of the proposed chamber based bearing design.

The 3-phenyl-1,4,2-dioxazol-5-one (PDO) Electrolyte Additive for Li(Ni0.6Mn0.2Co0.2)O2 and Li(Ni0.8Mn0.1Co0.1)O2 Lithium-Ion Cells

Electrolyte additives, as a small proportion of the electrolyte, greatly affect the performance of lithium-ion cells. This work performs a comparative study to reveal the difference between commercial 99.8% pure 3-phenyl-1,4,2-dioxazol-5-one (PDO) additive and lab-made 95% pure PDO in NMC622/graphite cells. In addition, a set of experiments were conducted to evaluate the performance of 99.8% pure PDO and its binary blends with vinylene carbonate (VC), 1,3,2-dioxathiolane-2,2-dioxide (DTD) or lithium difluorophosphate (LFO) in NMC811/graphite cells. 99.8% Pure PDO and 95% pure PDO show little difference in the NMC622 cells, with the latter presenting relatively better performance in the best-performing blends for long-term cycling and high-temperature storage tests. Considering all the tests including ultra high precision coulometry (UHPC) cycling, long-term cycling, and high-temperature storage, the NMC811 cells with 2%PDO+ 1%LFO outperformed the other PDO-containing cells. The PDO-based blends were confirmed to be more promising in cells with higher nickel content; that is, PDO could be a useful additive in high-nickel content cells.

Transient Interferometry of Ultra Precision Surface Based on Small Hole Point Diffraction

Transient Interferometry of Ultra Precision Surface Based on Small Hole Point Diffraction

Investigation of the tool influence function neighborhood effect in atmospheric pressure plasma processing based on an innovative reverse analysis method.

Ultra precision optical surfaces can be efficiently manufactured using a computer-controlled optical surfacing (CCOS) process. Based on the chemical reaction, atmospheric pressure plasma processing (APPP) is a promising deterministic CCOS technique and has great application prospect for the figuring processing as well as freeform generation. However, the plasma jet also works as the heat source, leading to the variation of substrate temperature field. This way, the tool influence function (TIF) is continuously changed, which leads to the nonlinear removal characteristic. Especially, it becomes much more complex when considering the neighboring dwell points, because they are thermally interacted. The conventional time-variant TIF model cannot accurately describe the practical TIF changes. In this paper, an innovative reverse analysis method is proposed to derive the practical TIF changes in APPP. First, the special problem of the TIF neighborhood effect is pointed out. The limitation of the conventional TIF model is analyzed with the assisted thermal model. Then, an innovative reverse analysis method is presented to derive the TIF changes from the practical removal, which is demonstrated with the simulation. Further, the proposed method is applied to the analysis of the TIF changes in APPP. To verify its feasibility, the experimental validation is undertaken, which proves its capability of deriving complex TIF changes.

Study on the Control of Micro-Environmental Parameters in Long Distance Laser Interferometry

Fluctuation in environmental parameters has become an important factor affecting the performance of ultra precision measurement. Aiming at the long-distance and high-speed laser interferometer measurement system, a method combining structure design and closed-loop control is proposed to reduce the measurement error caused by environmental parameters. The uniform pressure structure is designed, and the control system of micro environmental parameters is established. The simulation and experimental research on the uniformity of temperature and pressure on the optical path measured by laser interferometer are carried out. The simulation and experimental results show that this method can achieve temperature uniformity and stability above 0.01°C and pressure uniformity and stability above 1Pa, and can be widely used in micro environment parameter control of long-distance ultra precision measurement.

Freeform based hYperspectral imager for MOisture Sensing (FYMOS).

We present FYMOS, an all-aluminum, robust, light weight, freeform based, near infrared hYperspectral imager for MOisture Sensing. FYMOS was designed and built to remotely measure moisture content using spectral features from 0.7-1.7µm integrating an InGaAs sensor. The imaging system, operating at F/2.8, is based on the three-concentric-mirror (Offner) spectrograph configuration providing a spectral resolution of 8 nm optimized for broad spectral coverage with sufficient resolution to make assessments of water levels. To optimize the optical performance, whilst minimizing weight and size, the design incorporates a bespoke freeform blazed grating machined on a commercial 5 axis ultra precision diamond machine. We achieve a 30% improvement on the RMS wavefront error in the spatial and spectral fields compared to a conventional Offner-Chrisp design with similar aperture and the monolithic Primary/Tertiary mirror eases the manufacturing assembly whilst minimizing weight. We demonstrate the performance of FYMOS by measuring the evaporation rate of water on a soil sample and results are processed with a physical multilayer radiative transfer model (MARMIT) to estimate the mean water thickness.

Characteristic of SiC Slurry in Ultra Precision Lapping of Sapphire Substrates

A method is proposed in this paper to prepare a SiC slurry with SiC particles selected by an ultrasonic-assisted elutriation method to reduce substrate surface damage caused by abrasive particles during lapping. Sapphire substrate lapping experiments were carried out using the prepared SiC slurry, and the lapping performance of the slurry was analyzed. The experimental results show that the SiC particle size is a factor that directly affects the material removal rate and surface roughness Ra, of sapphire substrates. When a SiC slurry with a particle size of 630 nm was used, the material removal rate was 508 nm/h, and the surface roughness Ra was 1.9 nm; increasing the slurry concentration and the platen rotating speed can improve the material removal rate. In addition, the agglomeration of SiC particles in the slurry depends on the pH of the slurry. Efficient precision lapping of sapphire substrates can be achieved by selecting appropriately sized SiC particles and by adjusting the slurry pH to control the agglomeration and dispersion of SiC particlesto further reduce the scratches on the substrate surface during the lapping process.