Wear behavior of chromium nitride coating in dry condition at lower sliding velocity and load

Quantitative information about the contributions of individual cutting phenomena to linear roughness profiles may aid in optimizing processes with fewer expensive successive trial parts. Linear roughness profiles of metallic hard turned parts contain feed marks, each mark representing a snapshot in time of the state of the cut. This suggests that roughness measuring machines may be an attractive avenue for offline, inexpensive, non-destructive, quantitative evaluation of the time-dependent mechanisms active during the cut. Principal component analysis of feed marks reveals theoretically expected feed mark deformations without coercing the data by fitting. Novel in this paper, we show that those components of feed mark variability appear to correspond to radial and axial displacement of the cutting tool, ploughing, and side flow. Those components are sufficient to explain nearly all the variability between feed marks. The components are easily idealized in a general manner, and their influences on experimental profiles are quantified as percentage contributions to ordinary roughness parameters.     

Airbag tool polishing for aspherical glass lens molds

This paper presents a novel airbag tool polishing technique for small aspherical glass lens molds. For a mold material such as tungstencarbide, an ultra-precise grinding technique is used to generate the aspherical surface. However, the residual tool marks of the spiral pattern and scratch unavoidably develop on the mold surface. Therefore, post-polishing is required to obtain the optical surface. Footprinting by the superposition method without trajectory control was applied to polish the finely ground aspherical lens mold. A white light interferometer confirmed the tool mark removal effect. The final surface roughness was Ra 2nm. Microscopic observation also showed a cleaner surface without scratches.     

Spectral analysis of surface roughness features of a lapped ultraprecision single-point diamond machined surface

Single-point diamond turning of soft metals could provide a much shiny surface with an optimal feed rate; however, the machining mark would be left on the machined surface, which caused the roughness cannot be neglected. If the feed rate is too small, the roughness of the surface could be improved but the reflectiveness would be decreased because of damaging the profile. Therefore, it is necessary to develop a lapping method to reduce the roughness by removing the machining mark, while the reflectiveness can be kept at the original level simultaneously. In this study, the novel lapping method, using strands of wool fibers to deliver the abrasive slurry to rub against the lens, was proposed for removing the machining marks on the mold of a lenticular lens by lapping without damaging the profile of the mold. Even though the normal pressure applied by the wool strands onto the mold surface is very low, the coefficient of friction would be increased significantly with the application of the abrasive slurry. The combined effect was to provide a relatively large shear force to lap the surface with a minimal normal force. Therefore, the proposed method could theoretically avoid damaging the lens while effectively removing the irregularities that appeared on the surfaces. In order to evaluate the proposed lapping method, we firstly lapped the machining marks with different lapping parameters (speed, grit size, time, and pressure) to find out the relationship between these parameters and roughness with the same profile of the mold. Secondly, the optimal lapping parameters were designed based on the above lapping results to deduce the best lapping solution for processing the machining marks. Thirdly, the lapped surface profile of the mold was test by optical profiling system, and the features of the surface can be categorized into various spectral distribution groups. Finally, by comparing the variation of the spectral distribution groups, it is verified that based on our proposed methodology, selective removal of surface spectral groups of features becomes possible.     

Study on tool wear characteristics in diamond turning of reaction-bonded silicon carbide

Tool wear is one of the most critical problems in machining hard, brittle materials. In the present work, diamond turning experiments were performed on reaction-bonded silicon carbide, and the tool wear characteristics were investigated. A special kind of wear pattern, namely periodical groove wear, was identified on the flank face of the tool, where the periodicity of the microgrooves was the same as the tool feed. Geometrical analysis showed that the periodical groove wear was caused by the tool feed marks on the machined surface. Laser micro-Raman spectroscopy indicated that the high-pressure abrasive wear at the tool?Cworkpiece interface dominates the wear behavior, rather than the diamond?Cgraphite transformation. By swinging the tool around its curvature center during the cutting process, the periodical groove wear pattern was suppressed, and the tool wear was reduced significantly.     

辊筒模具微透镜阵列的慢刀伺服成形加工

目的：为实现辊筒模具表面微透镜阵列高效率、高精度加工,本文对微透镜阵列成形法加工轨迹的拟合方法和机床伺服参数的优化方法进行了理论与实验研究。首先,分析了微透镜阵列的原始轨迹特征,确定了过渡台阶的突变是微透镜表面振纹的主要诱因。其次,为保证加工轨迹二阶导数的连续性,本文提出了三次样条插值与傅里叶级数拟合拼接的方法优化加工轨迹。最后,在优化加工轨迹的基础上,通过调整伺服系统的前馈参数,提高了进给轴响应能力,减小了因驱动质量和阻尼效应而产生的跟踪误差。口径800μm、深度26.7μm的微透镜阵列加工实验表明,采用优化的刀具轨迹和伺服参数,机床加工效率可以达到8Hz,进给轴跟踪误差小于300nm,消除了微透镜阵列的表面振纹。微透镜单元口径的尺寸误差约为设计值的1.075%,随机检测结果表明口径尺寸变化范围为2μm,加工一致性良好。三次样条插值与傅里叶级数拟合优化的加工轨迹可有效抑制进给轴的振动,改善了微透镜阵列表面质量。     

Surface finishing method for tooth flank of heat-treated surface-hardened small gears using a gear-shaped tool composed of alumina-fiber-reinforced plastic

High-accuracy gears are necessary to ensure the strength and silence of compact geared motors. Heat-treated surface-hardened small gears are employed in the reducer of a compact geared motor. The heat treatment causes distortion, which deteriorates the gear accuracy. To remove this distortion, surface-hardened small gears are rehobbed with a carbide hob. The rehobbing makes a tool mark on the gear tooth surface. This tool mark leads not only to strength deterioration of the tooth surface, but also vibration and noise. Therefore, a surface finishing method that eliminates the tool mark is required. However, it is difficult to finish surface-hardened small gears. This study proposes a tooth surface finishing method for a surface-hardened small gear. The method employs a gear-shaped tool composed of alumina-fiber-reinforced plastic (ALFRP) and a surface finishing device with an oscillation/traverse system. The proposed method was used in an experiment to remove the tool mark on the gear tooth flank of a surface-hardened small gear rehobbed by the carbide hob. The effectiveness of this method was verified. In addition, the processing mechanism of the ALFRP gearshaped tool was analyzed by observing the tool and the chips.     

PHENOMENOLOGICAL ANALYSIS OF MATERIAL SIDE FLOW IN HARD TURNING: CAUSES, MODELING, AND ELIMINATION

Material side flow causes surface damage that has been observed and partly investigated over a period of several years. This paper presents a phenomenological analysis of material side flow in hard turning. First, material side flow is identified, characterized, and its causes classified. Then, the dependence of the material side flow on different process parameters is analyzed using the results of a comprehensive experimental investigation. Tool nose radius, tool wear, and feed are considered as the primary factors that initiate the occurrence of material side flow in finish turning of hardened steel. A new concept for modeling material side flow is then proposed. This model predicts the minimum chip thickness that allows the workpiece material in the vicinity of cutting to plastically flow at the side of the tool, instead of shearing. The value of the minimum chip thickness affects the size of material side flow on the feed marks. Based on the results obtained from the model, the feed and tool nose radius that eliminates/minimizes material side flow in hard turning are specified.     

视觉测量中圆形标志两种提取方法的比较

针对靶场视觉测量相机标定中圆形标志在复杂背景图像上的提取和定位问题,研究了两种不同的圆形标志提取方法,一种是基于感兴趣区域的交互式提取方法,另一种是基于图像灰度和几何形态学的提取方法。对两种方法的圆形标志提取过程进行了研究,并分别采用两种方法对视觉测量图像中的圆形标志进行提取实验,对两种方法的边缘提取效果和定位结果进行了对比,分析了两种方法的优势和不足。圆形标志的提取结果表明,第一种方法能够平滑地提取出圆形标志的边缘,但受圆形标志的成像情况影响较大,第二种方法边缘提取效果受圆形标志的成像情况影响较小,但提取出的边缘为锯齿形,部分圆形标志的像素点被误判为背景,与圆形标志的实际成像有一定误差。     

PHENOMENOLOGICAL ANALYSIS OF MATERIAL SIDE FLOW IN HARD TURNING: CAUSES,MODELING, AND ELIMINATION

ABSTRACT

Material side flow causes surface damage that has been observed and partly investigated over a period of several years. This paper presents a phenomenological analysis of material side flow in hard turning. First, material side flow is identified, characterized, and its causes classified. Then, the dependence of the material side flow on different process parameters is analyzed using the results of a comprehensive experimental investigation. Tool nose radius, tool wear, and feed are considered as the primary factors that initiate the occurrence of material side flow in finish turning of hardened steel. A new concept for modeling material side flow is then proposed. This model predicts the minimum chip thickness that allows the workpiece material in the vicinity of cutting to plastically flow at the side of the tool, instead of shearing. The value of the minimum chip thickness affects the size of material side flow on the feed marks. Based on the results obtained from the model, the feed and tool nose radius that eliminates/minimizes material side flow in hard turning are specified.     

Effect of tool tilt angle on machining strip width in five-axis flat-end milling of free-form surfaces

This paper examines the effect of tool tilt angle on machining strip width in the determination of optimal tool orientation and feed direction in five-axis flat-end milling. The machining strip width is evaluated using the swept profile of the flat-end mill, avoiding both local and global gouging of the tool. An optimization problem is formulated to maximize the machining strip width over feasible gouge-free tool orientations for a constant-feed direction. By solving the optimization problem and analyzing the geometry of the machining strip width, it is shown that identifying the optimal tool tilt angle, instead of following the common practice of setting the tool tilt angle as zero, can significantly increase the machining strip width, especially for 3D free-form surface machining. The optimization has also been extended to identify the optimal feed direction that maximizes the machining strip width at a given cutter contact (CC) point. The minimum curvature direction has been considered as the optimal feed direction at a CC point by researchers. Our results indicate that although the minimum curvature direction is mostly not the optimal feed direction in free-form surface machining, the minimum curvature direction does represent a good approximation of the optimal feed direction at a CC point, in particular for a free-form surface with low-curvature relative to the tool size.     

数控车床加工特殊螺纹接头产生颤纹的原因及对策

颤纹是特殊螺纹接头生产加工过程中普遍存在的现象,不仅影响特殊螺纹接头的表面质量,而且会导致特殊螺纹接头的各项性能恶化。本文从车床、刀具的刚性,试样的装夹情况,刀具的设计安装,加工工艺参数及加工方式的选择等几个方面对特殊螺纹接头加工过程中颤纹的产生原因进行了深入分析,并提出了相应的对策,为特殊螺纹接头的生产质量控制提供了一定参考。     

A method of using Hoelder exponents to monitor tool-edge wear in high-speed finish machining

Tool condition monitoring is increasingly important as a widespread application of automated, computer numerically controlled machining in a variety of modern industries. Although a significant amount of research on tool condition monitoring in machining has been conducted during the past few decades, the research is primarily focused on tool flank wear. Less attention is paid to tool-edge wear, which is a critical issue in high-speed finish machining where the feed rate is in the same magnitude as tool edge dimensions, and thus, the tool cutting edge is subjected to extensive mechanical and thermal deformation. The present study fills this important research gap in tool condition monitoring. This paper presents a method of monitoring tool-edge wear in the high-speed finish machining of an aerospace superalloy Inconel 718 by extracting Hoelder exponents from wavelet transform analysis of cutting vibrations. A total of 60 cutting experiments were conducted, covering a range of cutting speed and feed rate conditions. The experimental results show that cutting vibrations increase as tool-edge wear develops. Wavelet transform analysis can be employed to identify single local maxima of the cutting vibration signals. As tool-edge wear develops, the values of Hoelder exponents vary from 0.55 to 0.90. It is suggested that under the cutting conditions tested in the present study, 0.8 can be used as the threshold value of Hoelder exponents to differentiate severe and normal tool-edge wear.     

Forensic surface metrology: tool mark evidence

Over the last several decades, forensic examiners of impression evidence have come under scrutiny in the courtroom due to analysis methods that rely heavily on subjective morphological comparisons. Currently, there is no universally accepted system that generates numerical data to independently corroborate visual comparisons. Our research attempts to develop such a system for tool mark evidence, proposing a methodology that objectively evaluates the association of striated tool marks with the tools that generated them. In our study, 58 primer shear marks on 9?mm cartridge cases, fired from four Glock model 19 pistols, were collected using high-resolution white light confocal microscopy. The resulting three-dimensional surface topographies were filtered to extract all "waviness surfaces"-the essential "line" information that firearm and tool mark examiners view under a microscope. Extracted waviness profiles were processed with principal component analysis (PCA) for dimension reduction. Support vector machines (SVM) were used to make the profile-gun associations, and conformal prediction theory (CPT) for establishing confidence levels. At the 95% confidence level, CPT coupled with PCA-SVM yielded an empirical error rate of 3.5%. Complementary, bootstrap-based computations for estimated error rates were 0%, indicating that the error rate for the algorithmic procedure is likely to remain low on larger data sets. Finally, suggestions are made for practical courtroom application of CPT for assigning levels of confidence to SVM identifications of tool marks recorded with confocal microscopy.     

基于多波长散射光特性的铝合金超精密车削表面粗糙度测量方法研究

针对超精密车削表面，提出一种基于多波长散射光特性的表面粗糙度测量方法，以铝合金为例对该方法进行验证。首先建立超精密车削表面形貌—散射光模型并开展验证实验，定量实验结果证明建立的散射光模型平均误差仅为1%。基于散射光模型研究刀痕纹理方向、刀痕宽度(每转进给量)和刀痕高度(表面粗糙度峰谷值)对镜像光反射率的影响，研究结果证明表面粗糙度是影响镜像光反射率的关键因素。在此基础上进一步建立300～700 nm波长范围内镜像光反射率平均值和表面粗糙度之间的定量关系，基于超精密车削表面的测量结果对该定量关系进行验证。所提出新方法获得的粗糙度测量结果与原子力显微镜测量结果吻合，最大相对误差仅为7.5%。     

Experimental investigation of precision turning of Monel K-500 under dry conditions

In this paper, final surface accuracy in turning the super alloy Monel K-500 is studied. The experiments were conducted on the basis of the design of experiment methodology considering four inputs of tool nose radius, feed rate, depth of cut, and cutting speed, and three outputs of surface roughness, dimensional deviation, and tool wear. The aim of this work is to identify these three phenomena to achieve a desirable machined surface with acceptable finishing and the least deviation from nominal dimensions under different parametric conditions. It was observed that the quality of the machined surface in the direction of the machining length is not constant and, in some trials, the values of Ra increase considerably at the end of the machining length. The results show that cutting speed can improve surface accuracy, in a way that the more the cutting speed, the less the dimensional deviation. Less depth of cut and tool radius affect dimensional deviation as well. Although it has a small effect on dimensional deviation, feed rate plays the most important role in controlling tool wear. Finally, on the basis of Grey relational analysis, a simultaneous optimization is carried out on surface roughness, dimensional deviation, and tool wear values. In order to minimize these responses, optimal parametric conditions are presented. A satisfying correspondence was observed between the predicted results and the confirmation observations.     

Fundamental investigation on partially overlapped nano-cutting of monocrystalline germanium

Molecular dynamics simulations on partially overlapped nano-cutting of monocrystalline germanium with different feeds are carried out to investigate the surface topography, cutting force and subsurface deformation. The results indicate that the side-flow material piling up on the edges of tool marks is a decisive factor for the surface topography with the machining parameters in this study, ignoring the tool wear and machining vibration. In the partially overlapped nano-cutting, the lateral force is more affected by nominal depth of cut than by pitch feed with the value of feed being in some range. The atomic sights on the subsurface deformation show that the thickness of deformed layer after machining is much thinner than that after single cut with the same nominal depth of cut. Laser micro-Raman spectroscopy and cross-sectional transmission electron microscopy are used to detect the subsurface deformation of monocrystalline germanium after eccentric turning. The crystalline structure with defects rather than the amorphous germanium is observed in many areas of machined surface. Both molecular dynamics simulation and experimental results indicate that the amorphous-damage-less and even amorphous-damage-free machined surface can be achieved by partially overlapped nano-cutting.     

Prediction of surface roughness in CNC end milling by machine vision system using artificial neural network based on 2D Fourier transform

This paper presents a system for automated, non-contact, and flexible prediction of surface roughness of end-milled parts through a machine vision system which is integrated with an artificial neural network (ANN). The images of milled surface grabbed by the machine vision system could be extracted using the algorithm developed in this work, in the spatial frequency domain using a two-dimensional Fourier transform to get the features of image texture (major peak frequency F ₁, principal component magnitude squared value F ₂, and the average gray level G _a). Since F1 is the distance between the major peak and the origin, it is a robust measure to overcome the effect of lighting of the environment. The periodically occurring features such as feed marks and tool marks present in the gray-level image can be easily observed from the principal component magnitude squared value F _2. The experimental machining variables speed S, feedrate F, depth of cut D, and the response extracted image variables F ₁, F ₂, and G _a could be used as input data, and the response surface roughness R _a measured by Surfcorder SE-1100 (traditional stylus method) could be used as output data of an ANN ability to construct the relationships between input and output variables. The ANN was trained using the back-propagation algorithm developed in this work due to its superior strength in pattern recognition and reasonable speed. Using the trained ANN, the experimental result had shown that the surface roughness of milled parts predicted by machine vision system over a wide range of machining conditions could be got with a reasonable accuracy compared with those measured by traditional stylus method. Compared with the stylus method, the constructed machine vision system is a useful method for prediction of the surface roughness faster, with a lower price, and lower environment noise in manufacturing process. Experimental results have shown that the proposed machine vision system can be implemented for automated prediction of surface roughness with accuracy of 97.53%. The results are encouraging that machine vision system can be extended to many real-time industrial prediction applications.     

A new quantitative evaluation for characteristic of surface roughness in turning

With turning as the aim, a method for quantitatively evaluating the stability of cutting phenomena and a machining system from the machined surface profile (primary profile and roughness profile) is proposed, based on the hypothesis that when the ideal cutting is achieved, the form of the cutter should be perfectly copied on the machined surface and the process can be replicated. Therefore, if the form and the position of the cutter (normally known) are estimated, should be possible to quantitatively evaluate the stability of the cutting phenomena, including adhesion and built-up edge, based on the difference between the actual machined surface and the position of the cutter estimated. Moreover, due to the estimated positional accuracy of the adjoining cutting edges, it should be possible to evaluate the stability of the machining system based on the vibration and the accuracy of spindle rotation. In this study, a method for estimating a cutting edge during machining from a surface profile was developed. Furthermore, the proposed method was applied to evaluate three elements: a virtually ideal machining surface with good transferability, a machining surface with poor transferability, wherein feed marks are clear, and a surface with variable transferability and feed marks due to chatter or adhesion. The results indicated that the proposed method can be successfully used to extract these characteristics.     

EFFECT OF PROCESS PARAMETERS AND TOOL SHAPE ON THE MACHINABILITY OF A PARTICULATE FILLED-POLYMER COMPOSITE MATERIAL FOR RAPID TOOLING

This paper presents the results of an experimental study on the effects of machining parameters (cutting speed, feed, depth of cut) and tool shape on chip formation, surface topography, resultant cutting force and surface roughness produced in flat and ball end milling of the Ren Shape-Express 2000™ aluminum particulate filled-polymer composite material. This material is shown to exhibit a brittle-to-ductile transition in chip formation with decreasing cutting speed. The transition is explained by the strain-rate sensitivity of the polymer matrix and is found to correlate well with a corresponding change in the surface roughness. The absence of clear feed marks on the milled surface explains why molds made from the composite material require less hand polishing than machined metal molds. The influence of cutting conditions and tool shape (flat end vs. ball-nose) on the cutting force, surface roughness, and workpiece breakout are discussed and relevant comparisons with conventional metal and polymer machining are made.     

Optimisation of machining parameters for turning operations based on response surface methodology

Design of experiments has been used to study the effect of the main turning parameters such as feed rate, tool nose radius, cutting speed and depth of cut on the surface roughness of AISI 410 steel. A mathematical prediction model of the surface roughness has been developed in terms of above parameters. The effect of these parameters on the surface roughness has been investigated by using Response Surface Methodology (RSM). Response surface contours were constructed for determining the optimum conditions for a required surface roughness. The developed prediction equation shows that the feed rate is the main factor followed by tool nose radius influences the surface roughness. The surface roughness was found to increase with the increase in the feed and it decreased with increase in the tool nose radius. The verification experiment is carried out to check the validity of the developed model that predicted surface roughness within 6% error.