Dimensional analyses and surface quality of pulsed UV laser micro-machining of STAVAX stainless steel mold inserts

Laser micro-machining is a new, precise, and very flexible process in micro-mold manufacturing, especially for difficult to machine material, i.e., hardened steel. The aim of the work reported in this paper was to utilize response surface methodology to optimize the dimensional accuracy and surface finish for STAVAX stainless steel mold inserts in the pulsed UV laser micro-machining. The influence of laser machining parameters on the ablated depth and surface roughness of the machined mold inserts have been experimentally investigated. The parameters of insert quality are analyzed under varying laser power, pulse frequency, hatched spacing, scan rate, and number of passes. The settings of the laser micro-machining parameters are determined by using design of experiments method. The analysis of variance, and regression analyses are employed to find the optimal levels and to analyze the effect of the parameters on the depth accuracy values and surface finish. Confirmation experiments with the optimal levels of micro-machining parameters are carried out in order to illustrate the effectiveness of the multi-optimization method. The validity of regression approach to process optimization is well established.     

淬火45钢激光微加工工艺试验研究

采用激光表面微造型技术(LST),利用"单脉冲同点间隔多次"激光微造型工艺,在淬火45钢试样表面进行激光微造型工艺试验。主要进行脉冲重复次数与凹腔深度、脉冲重复频率与扫描速度对加工质量影响的试验研究,分析激光参数对加工质量的影响规律,得到了较优化的激光工艺参数组合。     

Zr基大块非晶合金在过冷液相区超塑性成形的摩擦行为及机理研究

采用双杯挤压方法研究了成形温度、应变速率等工艺参数对Zr55Al10Ni5Cu30块体非晶合金在过冷液相区塑性成形时模具和零件之间的摩擦行为的影响。采用有限元模拟方法获得大块非晶合金双杯挤压的摩擦因数标定曲线,有限元模拟中非晶合金的变形采用Kawamura的本构模型,将高温压缩实验的数据拟合,获得本构模型中的参数,结果表明非晶合金在过冷液相区内变形的摩擦因数在0.2~0.7之间。当应变速率较低时,随着温度的升高,摩擦因数总体上降低;而当应变速率较高时,随着温度的升高,摩擦因数先略有上升,然后急剧下降。当温度较低时,随着应变速率增大,摩擦因数显著增大,而在高温时,随着应变速率增大,摩擦因数略微有所减小。按照现代摩擦理论对非晶合金在过冷液相区内成形的摩擦机理进行了分析,认为黏着是摩擦的主导因素。     

铣削加工粗糙度的智能预测方法

提出了一种基于最小二乘支持向量机的铣削加工表面粗糙度智能预测方法.首先进行了铣削工艺参数对工件表面粗糙度影响的正交实验,再通过对主轴转速、进给速率和切削深度三因素,以及各因素之间交互三水平实验的数据分析,找出了铣削工艺参数对工件表面粗糙度影响的一些规律.利用最小二乘支持向量机算法建立了铣削预测模型,通过该模型能在有限实验基础上利用工艺参数方便地得到粗糙度预测值.实际预测表明,在相同情况下,该模型构造速度比反向传播神经网络建模预测方法高2个～3个数量级,预测精度高10倍左右.     

Effect of the process parameters on the three-dimensional shape of molten pool during full-penetration laser welding process

Slow tool servo (STS) turning is superior in machining precision and in complicated surface. However, STS turning is a complex process in which many variables can affect the desired results. This paper focuses on surface roughness prediction in lenses STS turning. An exponential model, based on the five main cutting parameters including tool nose radius, feed rate, depth of cut, C-axis speed, and discretization angle, for surface roughness prediction of lenses is developed by means of orthogonal experiment regression analysis. Meanwhile, a prediction model of surface roughness based on least squares support vector machines (LS-SVM) with radial basis function is constructed. Orthogonal experiment swatches are studied, and chaotic particle swarm optimization and leave-one-out cross-validation are applied to determine the model parameters. The comparison of LS-SVM model and exponential model is also carried out. Predictive LS-SVM model is found to be capable of better predictions for surface roughness and has absolute fraction of variance R² of 0.99887, the mean absolute percent error e_M of 8.96 %, and the root mean square error e_R of 10.68 %. The experimental results and prediction of LS-SVM model show that effects of tool nose radius and feed rate are more significant than that of depth of cut on surface roughness of lenses turning.     

Experimental investigation of laser transformation hardening of low alloy steel using response surface methodology

In this research, a systematic investigation on laser transformation hardening (LTH) process is carried out on high-strength low-alloy medium carbon steel, EN25 using design of experiments (DOE). The effect of input process parameters like laser power, travel speed over the response hardened width (HW), hardened depth (HD), and hardened area (HA) are analyzed. The experimental trials are conducted based on the design matrix obtained from the 3^k full factorial design (FFD) using a 2 kW continuous wave Nd:YAG laser power system. A quadratic regression model is developed to predict the responses using response surface methodology (RSM). Based on the developed mathematical models, the direct and interaction effects of the process parameters on LTH are investigated. The optimal hardening conditions are identified to maximize the HW and minimize the HD and HA. The results of the validation test show that the experimental values quite satisfactorily agree with the predicted values of the mathematical models and hence, the models can predict the response adequately.     

丝杠冷滚打成形参数控制研究

建立了丝杠冷滚打成形的有限元模型,使用ABAQUS软件模拟其成形过程。首先在仿真结果的基础上,设计正交试验,研究冷滚打过程中工艺参数对滚打深度和隆起高度的影响关系;然后分别建立滚打深度和隆起高度与工艺参数之间的多元回归模型,并进行显著性检验;最后利用自行设计的滚打装置进行丝杠冷滚打试验,验证了模型的有效性。研究结果为通过控制工艺参数形成精确的零部件轮廓提供理论基础,对丝杠冷滚打成形有重要的指导意义。     

基于最小二乘支持向量机的铣削加工表面粗糙度预测模型

在分析以往所建立的表面粗糙度预测模型方法不足的基础上，将一种基于最小二乘支持向量机的预测模型引入铣削加工领域，并给出了相应的步骤和算法。该模型能方便地预测铣削加工参数对加工表面粗糙度的影响，并能利用有限的试验数据得出整个工作范围内的表面粗糙度预测值，有助于准确认识已加工表面质量随铣削参数的变化规律。通过具体实例及与其他几种预测方法的对比表明，在相同样本条件下，其模型构造速度比标准支持向量机方法高1～2个数量级，模型预测误差约为支持向量机方法的40％，预测精度比常规BP模型高1个数量级。因此，基于最小二乘支持向量机方法建模速度快、预测精度高、适合加工表面粗糙度预测。     

The Effect of Laser Texturing of Steel Surfaces and Speed-Load Parameters on the Transition of Lubrication Regime from Boundary to Hydrodynamic

Laser surface texturing (LST) is an emerging, effective method for improving the tribological performance of friction units lubricated with oil. In LST technology, a pulsating laser beam is used to create thousands of arranged microdimples on a surface by a material ablation process. These dimples generate hydrodynamic pressure between oil-lubricated parallel sliding surfaces. The impact of LST on lubricating-regime transitions was investigated in this study. Tribological experiments were carried out on pin-on-disk test apparatus at sliding speeds that ranged from 0.15 to 0.75 m/s and nominal contact pressures that ranged from 0.16 to 1.6 MPa. Two types of oil with different viscosities (54.8 cSt and 124.7 cSt at 40°C) were evaluated as lubricants. Electrical resistance between flat-pin and laser-textured disks was used to determine the operating lubrication regime. The test results showed that laser texturing expanded the range of speed-load parameters for hydrodynamic lubrication. LST also reduced the measured friction coefficients of contacts that operated under the hydrodynamic regime. The beneficial effects of laser surface texturing are more pronounced at higher speeds and loads and with higher viscosity oil.     

Prediction of surface roughness in end face milling based on Gaussian process regression and cause analysis considering tool vibration

Surface roughness is a technical requirement for machined products and one of the main product quality specifications. In order to avoid the costly trial-and-error process in machining parameters determination, the Gaussian process regression (GPR) was proposed for modeling and predicting the surface roughness in end face milling. Cutting experiments on C45E4 steel were conducted and the results were used for training and verifying the GPR model. Three parameters, spindle speed, feed rate, and depth of cut were considered; the experiment results showed that depth of cut is the main factor affecting the surface roughness and regression results showed that the GPR model has a good precision in predicting the surface roughness in different cutting conditions. The prediction accuracy was nearly about 84.3 %. Based on the GPR prediction model, 3D-maps of surface roughness under various cutting parameters could be obtained. It is very concise and useful to select the appropriate cutting parameters according to the maps. As experimental results did not conform to the empirical knowledge, frequency spectrums of the tool were analyzed according to the 3D-maps, it was found that tool vibration is also a crucial factor affecting the machined surface quality.     

梯形流道灌水器流量定量设计研究

取梯形流道灌水器的6个关键参数为因素,采用均匀设计试验方法设计出18组灌水器结构,利用光固化成形技术快速制作出各参数组合的灌水器试验样件并进行水力性能测试。分别对流量系数和流态指数进行回归分析,结果表明流量系数与6个参数之间表现为幂函数关系,流态指数主要体现为6个参数之间的二次函数关系。通过另外设计4组灌水器结构并利用其实测数据对两回归模型进行验证,结果表明此模型能很好预测流量与压力之间的关系,研究结果为此类灌水器流量的定量设计提供了经验公式。     

An Experimental Study and Statistical Analysis of the Effect of Laser Pulse Energy on the Geometric Quality During Laser Precision Machining

In laser precision machining, process parameters have critical effects on the geometric quality of the machined parts. Due to the nature of the interrelated process parameters involved, an operator has to make a host of complex decisions, based on trial-and-error methods, to set the process control parameters related to the laser, workpiece material, and motion system. The objective of this work is to investigate experimentally the effect of laser pulse energy on the geometric quality of the machined parts in terms of accuracy, precision, and surface quality. Experimental study of formation of machined craters on thin copper foil with variation in laser pulse energy, the geometry and the surface topology of craters is presented. The geometrical parameters were measured and statistically analyzed with respect to incident pulse energy. Statistical analysis including pattern recognition was employed to analyze the experimental data systematically and to serve proper selection of the process parameters to achieve the desired geometric quality of the machined parts. Plausible trends in the crater geometry with respect to the laser pulse energy are discussed. The technique has been verified experimentally on simple geometrical features such as circles and grooves, and the geometric quality is evaluated.     

Development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis

Cutting tool wear is a critical phenomenon which influences the quality of the machined part. In this paper, an attempt has been made to create artificial flank wear using the electrical discharge machining (EDM) process to emulate the actual or real flank wear. The tests were conducted using coated carbide inserts, with and without wear on EN-8 steel, and the acquired data were used to develop artificial neural networks model. Empirical models have been developed using analysis of variance (ANOVA). In order to analyze the response of the system, experiments were carried out for various cutting speeds, depths of cut and feed rates. To increase the confidence limit and reliability of the experimental data, full factorial experimental design (135 experiments) has been carried out. Vibration and strain data during the cutting process are recorded using two accelerometers and one strain gauge bridge. Power spectral analysis was carried out to test the level of significance through regression analysis. Experimental results were analyzed with respect to various depths of cut, feed rates and cutting speeds.     

An Experimental Study and Statistical Analysis of the Effect of Laser Pulse Energy on the Geometric Quality During Laser Precision Machining

In laser precision machining, process parameters have critical effects on the geometric quality of the machined parts. Due to the nature of the interrelated process parameters involved, an operator has to make a host of complex decisions, based on trial‐and‐error methods, to set the process control parameters related to the laser, workpiece material, and motion system. The objective of this work is to investigate experimentally the effect of laser pulse energy on the geometric quality of the machined parts in terms of accuracy, precision, and surface quality. Experimental study of formation of machined craters on thin copper foil with variation in laser pulse energy, the geometry and the surface topology of craters is presented. The geometrical parameters were measured and statistically analyzed with respect to incident pulse energy. Statistical analysis including pattern recognition was employed to analyze the experimental data systematically and to serve proper selection of the process parameters to achieve the desired geometric quality of the machined parts. Plausible trends in the crater geometry with respect to the laser pulse energy are discussed. The technique has been verified experimentally on simple geometrical features such as circles and grooves, and the geometric quality is evaluated.     

基于响应曲面法的轴承钢GCr15高速外圆磨削参数优化

为充分发挥轴承钢GCr15优越的材料性能,保证GCr15轴承等产品的加工质量和加工效率,开展了高速外圆磨削参数优化研究。选用立方氮化硼（CBN）砂轮进行GCr15的高速外圆磨削响应曲面试验,根据试验结果建立磨削力、磨削温度、变质层深度等磨削结果的回归模型。结合回归模型与磨粒的最大未变形切屑厚度模型,综合分析砂轮线速度、工件速度、磨削深度等磨削参数对磨削结果的影响规律。以磨削结果综合最小为目标,进行磨削参数的多目标优化,通过试验验证优化模型和优化结果的正确性。     

Investigation of laser and process parameters for Selective Laser Erosion

The process of Selective Laser Erosion (SLE) was investigated to study the effects of different process and laser parameters on the process outputs such as surface quality and erosion rate. The SLE process is a direct method to remove material in a layer-by-layer fashion due to high energy densities provided by the laser beam. In addition to its direct use as a subtractive manufacturing method, SLE may be used in combination with layer-additive techniques such as Selective Laser Melting (SLM). Such combination mainly makes sense when both processes can be performed with the same laser. However, one of the major problems involved in SLE process is the high number of the laser and process parameters (laser power, pulse frequency, scan speed, scan spacing, ambient atmosphere, etc.) and the complexity of the relations between them which has not yet been investigated completely.This paper presents an overview of the laser erosion process with nano-second Nd:YAG laser pulses and the results of several single-factor experiments that were carried out to determine the influence of the major parameters on the depth of erosion per layer and surface roughness. Additionally, the relations between the parameters are studied to investigate the interactions between them. The results from single-factor experiments showed that some relations were highly governed by the power intensity of the laser beam and also that cross interactions between the parameters play an important role on the output characteristics. The paper explains how multiple parameters (spot size, pulse frequency, scan speed, scan spacing) can be combined to define two indirectly controlled geometrical parameters, namely the scan and pulse overlap factors. Those two parameters allow calculating the number of hits of the laser beam on a same location on the workpiece possible which is the first step in physical modeling the topography of the surface left behind.     

K9玻璃磨削亚表面损伤深度预测模型及实验研究

基于压痕实验原理,建立了K9玻璃亚表面损伤深度预测模型。为获得预测模型中的未知参量,开展了K9玻璃磨削实验。利用激光扫描共聚焦显微镜检测工件磨削后的表面粗糙度值,利用扫描电镜检测磨削后的工件表面微观形貌和亚表面损伤层形貌,分析了工艺参数对表面粗糙度值和亚表面损伤深度的影响规律。考查了工艺参数对法向磨削力的影响规律,并根据实验数据,采用多元线性回归拟合法得到法向磨削力的经验公式,进而确定了亚表面损伤深度预测模型的参数。模型预测值与实验值具有较好的一致性,表明预测模型具有一定的可靠性。     

电液束加工小孔质量的试验研究

介绍了电液束加工的试验装置。通过安排正交试验探索电压、电流、占空比、加工间隙、加工时间等工艺参数对加工孔径、孔深的影响。根据测出的电流波形求解出总电量,计算出电流效率大于100%,对此试验现象也进行了初步的分析。     

Bearing degradation process prediction based on the PCA and optimized LS-SVM model

Bearing degradation process prediction is extremely important in industry. This paper proposed a new method to achieve bearing degradation prediction based on principal component analysis (PCA) and optimized LS-SVM method. Firstly, the time domain, frequency domain, time–frequency domain features extraction methods are employed to extract the original features from the mass vibration signals. However, the extracted original features still with high dimensional and include superfluous information, the multi-features fusion technique PCA is used to merge the original features and reduce the dimension, the typical sensitive features are extracted. Then, based on the extracted features, the LS-SVM model is constructed and trained for bearing degradation process prediction. The pseudo nearest neighbor point method is used to determine the input number of the model. The particle swarm optimization (PSO) is used to selected the LS-SVM parameters. An accelerated bearing run-to-failure experiment was carried out, the results proved the effectiveness of the methodology.     

Influence of graphite and machining parameters on the surface roughness of Al-fly ash/graphite hybrid composite: a Taguchi approach

This paper presents an experimental investigation on the surface roughness of pure commercial Al, Al-15 wt% fly ash, and Al-15 wt% fly ash/1.5 wt% graphite (Gr) composites produced by modified two-step stir casting. The effect of reinforcements and machining parameters such as cutting speed, feed rate, and depth of cut on surface roughness, which greatly influence the performance of the machined product, were analyzed during turning operation. The optimum machining parameters were found in minimizing the surface roughness of the materials by using the Taguchi and ANOVA approach. Results show that the presence of the fly ash particles reduces the surface roughness of composites compared with pure Al. The inclusion of 1.5 wt% Gr in the Al-fly ash composite reduces the surface roughness considerably. A scanning electron microscopy investigation was carried out on the machined surfaces of the tested materials. Confirmation tests were performed to validate the regression models.