A new representation with probability distribution for nanometric surface roughness in ultra-precision machining

Ultra-precision machining (UPM) commonly produces nanometric surface roughness (NSR), which is governed by high-frequency components with tool marks sensitive to noise. Its spacing features (SF) majorly affect optical quality by diffraction and interference. However, the ISO SR standard cannot effectively represent SF. In this study, a new representation for SF was developed by evaluating surface derivative, as extra SR parameters. Probability distribution with the 95–99 rule was adopted to reduce noise effects. The results were found that the extra SR parameters well represents SF and are sensitive to spatial frequency. Probability distribution is an efficient means of reducing noise effects. Significantly, the proposed method is simple and efficient to represent SF of NSR in UPM.     

A dynamic surface topography model for the prediction of nano-surface generation in ultra-precision machining

Materials induced vibration has its origin in the variation of micro-cutting forces caused by the changing crystallographic orientation of the material being cut. It is a kind of self-excited vibration which is inherent in a cutting system for crystalline materials. The captioned vibration results in a local variation of surface roughness of a diamond turned surface. In this paper, a dynamic surface topography model is proposed to predict the materials induced vibration and its effect on the surface generation in ultra-precision machining. The model takes into account the effect of machining parameters, the tool geometry, the relative tool–work motion as well as the crystallographic orientation of the materials being cut. A series of cutting experiments was performed to verify the performance of the model and good correlation has been found between the experimental and simulation results.     

Prediction of surface roughness in CNC turning by model-assisted response surface method

Various statistical approaches such as classical regression and modern machine learning methods have been applied to measurement data for estimating the status of manufacturing processes, which is now boosted by the movement of Internet of Things (IoT). In this study, we attempt to integrate an analytical tool model of surface roughness and measurement data of CNC turning to develop a modeling approach which does not depend too much on data, but also effectively uses existing analytical models. As in previous researches, we use cutting speed, feed rate, depth of cut and three acceleration components from an accelerometer to predict surface roughness. Co-Kriging method is employed to integrate the above measurements and a well-known model of surface roughness in turning. It was confirmed that the approach improved the prediction accuracy when only small amount of data is available for model construction. Meanwhile, the accuracy of ordinary Kriging method, which only depends on data, is suitable when measurement data sufficiently spans the parameter space, being expected that it may be rare in actual operations. We also attempted to detect outlier of measurements using the Co-Kriging method, which might be a non-trivial task when there is no additional information to evaluate the validity of the measurement data.     

Effects of tool overhang on selection of machining parameters and surface finish during diamond turning

In precision machining leading to nano-metric surface finish, selection of the suitable machining parameters is a critical task. To ensure the desired surface quality, one needs to optimally select the machining parametric matrix. Towards this effort, this paper adds another critical parameter in terms of tool overhang. A well-defined set of machining exercises is carried out with different tool overhangs and machining parameters. In this investigation, an attempt has been made to locate the optimum range of tool overhang with minimum tool vibrations. The interaction between tool overhang with other parameters is also thoroughly investigated. Another important focus of this study is to find out the optimum machining parameters for the situations where it is not possible to select an optimum tool overhang. One such situation occurs when a steep concave parabolic surface needs to be fabricated. In this case a large tool overhang has to be selected. Power spectral density distribution analysis of surface roughness for different tool overhangs is performed to find out significant parameters and their degree of contribution to surface roughness. Analysis of variance is also applied to ascertain statistically significant factors contributing to surface roughness. To model the surface roughness, response surface methodology is being used. The model has been verified by conducting a series of experiments and a steep concave parabolic surface is developed by following the predictions of the developed model.     

金刚石飞切加工微结构表面的表面粗糙度研究

为了获得具有纳米级表面质量的微结构表面,利用‘Nanosys-300’超精密复合加工系统实现了微结构表面的三维金刚石飞切加工,研究了主轴转速、进给量以及背吃刀量对微结构表面粗糙度的影响。通过对理论表面粗糙度分析可知：金刚石飞切加工微结构时理论表面粗糙度沿法线方向并没有变化,而沿进给方向存在着周期变化。减小进给量f和金刚石飞刀前端角ε或增大切削半径可以降低理论粗糙度值。实验分析结果表明：表面粗糙度值Ra随进给量的增加而增加,主轴转速对Ra影响不大。切削PC时,在5μm-40μm范围内,Ra随背吃刀量的增加而增加;而切削LY12时,在2μm-10μm范围内,Ra随背吃刀量的增加而减小。实验中Ra最好可达38nm（LY12）和43nm（PC）。最后利用优化工艺参数加工出了微沟槽阵列和微金字塔矩阵微结构。     

A novel robust Gaussian filtering method for the characterization of surface generation in ultra-precision machining

A lot of research work has been focused on the study of the surface generation mechanisms in order to predict the surface topography and provide the optimal machined parameters based on the experiential understanding of relationship of machined conditions and surface features. Although the formation of novel geometrical product specification (GPS) and verification framework system promotes the relevant research work to new characterization methods and draft of international standards, relative little research work was conducted on the application of surface characterization techniques to ultra-precision machining which is very important to evaluate the surface quality. In this paper, a novel robust Gaussian filtering method (RGF) is proposed and used to characterize the surface topography of ultra-precision machined surfaces. Cubic B-spline and M-estimation are used to make the method reliable and robust. Based on the property comparisons of classical weighting functions, a novel auto-developed robust weighting function (ADRF) is defined to improve the robustness of RGF. To verify the characterization feasibility of the proposed method, computer simulation is used and then the real ultra-precision machined surfaces are analyzed. The experimental results indicate that the RGF method cannot only separate the surface components effectively on the whole measured area and but also eliminates the influence of freak outliers.     

超精密车削表面微观形貌对光学特性影响研究

为了给超精密车削加工表面的光学性能评价提供参考,指导实际加工过程的优化,本文对表面形貌和其光学性能之间的关系进行深入研究。对于仅有理想刀痕的表面所产生的重影现象,采用阈值分析和粗糙度散射理论两方面进行分析。阈值分析是指先计算单段圆弧刀痕的散射特性,再根据周期性结构对光的调制性,可以求得加工出镜面对刀尖圆弧半径和进给率（主轴每转的进给距离）选择的大约临界值要求。在入射光波长500 nm的情况下,当刀尖圆弧半径选择500 um时,可以算得阈值进给率为19 um。粗糙度散射理论分析则是通过电场积分公式—Stratton-Chu公式进行更精确的计算。最终得出结论,对于超精车加工得到的表面,当从入射光的非镜面方向,尤其是一极大散射方向观察不到光强时,则可以认为加工出了镜面效果。     

A neural-network-based methodology for the prediction of surface roughness in a turning process

A neural-network-based methodology is proposed for predicting the surface roughness in a turning process by taking the acceleration of the radial vibration of the tool holder as feedback. Upper, most likely and lower estimates of the surface roughness are predicted by this method using very few experimental data for training and testing the network. The network model is trained using the back-propagation algorithm. The learning rate, the number of neurons in the hidden layer, the error goal, as well as the training and the testing dataset size, are found automatically in an adaptive manner. Since the training and testing data are collected from experiments, a data filtration scheme is employed to remove faulty data. The validation of the methodology is carried out for dry and wet turning of steel using high speed steel and carbide tools. It is observed that the present methodology is able to make accurate prediction of surface roughness by utilising small sized training and testing datasets.     

Influence of machining parameters on surface roughness in finish cut of WEDM

Surface roughness is significant to the finish cut of wire electrical discharge machining (WEDM). This paper describes the influence of the machining parameters (including pulse duration, discharge current, sustained pulse time, pulse interval time, polarity effect, material and dielectric) on surface roughness in the finish cut of WEDM. Experiments proved that the surface roughness can be improved by decreasing both pulse duration and discharge current. When the pulse energy per discharge is constant, short pulses and long pulses will result in the same surface roughness but dissimilar surface morphology and different material removal rates. The removal rate when a short pulse duration is used is much higher than when the pulse duration is long. Moreover, from the single discharge experiments, we found that a long pulse duration combined with a low peak value could not produce craters on the workpiece surface any more when the pulse energy was reduced to a certain value. However, the condition of short pulse duration with high peak value still could produce clear craters on the workpiece surface. This indicates that a short pulse duration combined with a high peak value can generate better surface roughness, which cannot be achieved with long pulses. In the study, it was also found that reversed polarity machining with the appropriate pulse energy can improve the machined surface roughness somewhat better compared with normal polarity in finish machining, but some copper from the wire electrode is accreted on the machined surface.     

超声振动切削超薄壁精密零件的粗糙度试验研究

对直径为 47.75mm壁厚为 0 .8～ 1 .5mm的照相机导向镜筒零件进行普通和超声车削试验 ,研究了各切削参数对此类超薄壁零件表面粗糙度的影响规律 ,也试验研究了超声振动切削时切削液及车刀对表面粗糙度的影响     

超声波振动挤压加工表面粗糙度试验研究

对超声波振动挤压加工中工件表面粗糙度的形成机理及规律进行了试验研究及分析,并对其主要工艺参数进行优选.     

Case study of surface micro-waves in ultra-precision raster fly cutting

In ultra-precision raster fly cutting (UPRFC), very high frequency microwaves in the range of 3.42 MHz–6.36 MHz are found on the machined surface. This study conducted a series of theoretical and experimental investigations to discover the origin of these microwaves and how they might be suppressed. Research results show that: (i) microwaves on the machined surface are caused by the material sliding during the chip formation in UPRFC; (ii) owing to the inconsistent thickness of chips along their length direction, the microwaves accumulate at the surface-exit in each feed length; and (iii) chip thickness and tool wear change the length and distribution of the microwaves. This research provides a deep insight into the formation of microwaves along with suggestion on how to suppress them.     

高速车削工件表面形貌及其粗糙度特征的试验研究

借助于扫描电镜照片、已加工样品表面形貌轮廓描绘和试验数据处理等手段,对高速车削工件已加工表面形貌与其表面粗糙度之间的关系以及它们的形成特征进行了分析研究.研究结果表明,切削速度和被切削材料的硬度是决定高速车削过程中被切削层材料变形和已加工表面形貌及其表面粗糙度形成的主要因素,随着被切削材料硬度和切削速度的提高,工件已加工表面质量在一定程度上得到了改善.在已加工表面上出现了犁垄和高速加工所特有的熔融金属涂抹现象,由此决定着已加工表面粗糙度值的变化.     

Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method

This study focuses on optimizing turning parameters based on the Taguchi method to minimize surface roughness (Ra and Rz). Experiments have been conducted using the L9 orthogonal array in a CNC turning machine. Dry turning tests are carried out on hardened AISI 4140 (51 HRC) with coated carbide cutting tools. Each experiment is repeated three times and each test uses a new cutting insert to ensure accurate readings of the surface roughness. The statistical methods of signal to noise ratio (SNR) and the analysis of variance (ANOVA) are applied to investigate effects of cutting speed, feed rate and depth of cut on surface roughness. Results of this study indicate that the feed rate has the most significant effect on Ra and Rz. In addition, the effects of two factor interactions of the feed rate-cutting speed and depth of cut-cutting speed appear to be important. The developed model can be used in the metal machining industries in order to determine the optimum cutting parameters for minimum surface roughness.     

A study on surface roughness in ion-beam machining

This paper presents results on the influence of various machining conditions, namely machining time, (argon) ion energy, ion current density and beam angle, on surface roughness and machining depth for a high chromium — high carbon steel (SKD-1). The roughness characteristics are discussed from the measurement of surface asperities and the analysis of chromium density. In addition, as a method to obtain good surface roughness, the floating method which applies a positive charge to the workpiece, is tested.     

球头立铣刀铣削加工表面粗糙度仿真技术研究

铣削加工表面粗糙度的形成与铣刀和工件振动、主轴偏心、刀具磨损、刀具变形等物理和几何因素有关。多年来中外学者针对各种影响因素建立了“相对单一”的数学模型。这些数学模型只考虑了一种或两种影响因素,还没有建立起描述物理和几何变化过程的综合数学模型,为此对这些相关因素进行了深入研究,建立了基于球头立铣刀的铣削加工表面粗糙度仿真的整体数学模型。从而为虚拟数控加工仿真提供技术支撑。     

微小型车铣加工表面粗糙度正交试验研究

铣车转速比、工件转速、轴向进给量以及切削深度是车铣加工中相对独立的四个重要切削参数.运用正交试验法研究微小型零件车铣加工表面粗糙度与上述四因素的关系.试验数据分析结果表明,该四因素对表面粗糙度的影响程度从大到小依次为:铣车转速比、轴向进给量、工件转速、切削深度.而且转速比的提高对粗糙度值的影响是单调的,转速比越高粗糙度越低.这一结论也与单因素试验结果相吻合.由试验结果分析还得到各切削参数的优化匹配关系.     

基于神经网络的高速铣削表面粗糙度预报

提出利用神经网络进行高速铣削表面粗糙度预报的方法,给出了具体的网络实现过程,应用灵敏度剪枝算法克服了网络隐层难以确定的问题,仿真结果表明该方法的有效性,对高速加工切削参数的选择和表面质量控制具有指导意义。     

Simulation and measurement of surface roughness via grey scale image of tool in finish turning

Study on the surface roughness of specimen is a significant field of research because this parameter affects the performance of the machined parts. Meanwhile, the evaluation of surface roughness of specimens using a vision system via the images captured from the specimen is an interesting method which is widely used. Although the effect of flank and crater wear has been investigated extensively in the past researches on surface profiles, some reports indicated that, in finish turning, the nose radius wear has a greater effect on the surface profile of specimen. Although, vibration can affect the surface profile of a specimen in rough turning, the final surface profile in the product used is usually shaped by finish turning that may not be affected by vibration using the robust machine tool. In this work, a machine vision was used to capture the images of the tool tip in-cycle. The 2-D images of the nose area of tool tips were used to simulate the surface profile of specimens in finish turning. The simulated images of specimens in a range of machining condition were detected using the algorithm of this work. The results showed that this method can be used successfully to simulate and evaluate the surface profile of a specimen in finish lathe machining as a fingerprint of the tool tip. This method can be used for forecasting the final surface profile in order to control the performance of products.     

凸圆弧前刀面铣刀头超精铣削时主要参数对粗糙度及残留面积的影响

通过详细推算,给出凸圆弧前刀面金刚石铣刀头超精铣削平面时的理论表面粗糙度和切削残留面积的计算公式.利用所得的公式,进一步分析了凸圆弧半径、走刀、后角及安装误差角等主要参数对它们的影响.其Ra值可达几个纳米、P-V值达亚微米级.