石英玻璃固结磨料研磨工艺参数响应面模型的研究

目的 通过优化工艺参数,充分挖掘固结磨料研磨加工的优势.方法 采用固结磨料研抛垫对石英玻璃进行研磨,以材料去除率(MRR)和表面粗糙度(Ra)为评价指标,采用3因素3水平的响应曲面法,探索工件转速、研磨压力、研磨液流速三个工艺参数对固结磨料垫加工特性的影响规律.建立三个工艺参数作用下的MRR模型和Ra模型,结合响应曲面及其等高线,获得工艺参数变量两两复合的影响规律和各目标下的最优工艺参数.最后,对最优工艺参数进行实验验证.结果 实验结果及其分析表明,以最大材料去除率为目标的最佳工艺参数为:转速90 r/min,压力20.685 kPa,研磨液流速60 mL/min.以最小表面粗糙度为目标的最佳工艺参数为:转速100 r/min,压力20.685 kPa,研磨液流速80 mL/min.最优工艺的加工性能预测值为34.5 nm/min和38.5 nm,验证实验结果为37.6 nm/min和39.4 nm,二者的误差值在合理范围内.结论 研抛工艺参数的响应面模型具有良好的预测能力,预测误差很小,最优工艺参数下,工件表面平整光滑,没有明显的凹坑和粗大划痕.     

湿式主轴式滚磨光整加工中铝合金 试件的材料去除行为研究

目的 针对湿式主轴式滚磨光整加工工艺,提出适用于铝合金试件光整加工的材料去除模型。方法 通过FLUENT两相流模块模拟不同参数下p?v值,用响应曲面法拟合4个主要参数和p?v的多元回归模型,在此基础上,基于Preston方程建立修正的材料去除模型,进行加工实验,探究工件的MRR、加工后Ra和表面形貌之间的关系。结果 方差分析中,工件轴心距筒壁距离和滚筒转速项的P<0.05,两者对MRR影响显著,且前者与MRR负相关,后者与MRR正相关。对模型进行加工实验验证,工件MRRth和MRRex的平均相对误差仅为6.32%,证明模型的有效性。随工件MRR的递增,加工后Ra值先减后增,MRR值为21 mg/h时,Ra为0.816 µm,工件刀纹仍很明显;MRR值为59 mg/h时,Ra达到最低值0.472 µm,工件刀纹完全去除,表面纹理细致平整,加工效果最佳;当MRR达极值时,Ra为0.693 µm,表面纹理变得粗糙不平,由于滚抛磨块的加工能力过强,导致加工效果较差。结论 建立了以工艺参数为自变量的材料去除模型,为选择参数提供一定的理论依据,且实验研究得出,加工能力与加工效果之间不存在正向相关性。     

基于多源数据融合的半导体晶片CMP抛光材料去除率预测

目的 对半导体晶片抛光过程中的工艺参数、耗材使用量、抛光垫状态参数等多源数据预处理后进行数据融合,建立材料去除率(MRR)预测模型,为实现半导体晶片抛光加工工艺的决策和处理奠定基础。方法 研究晶片抛光加工中的数据特点及数据融合需求,提取数据集中每个晶片加工过程中的统计特征并生成新数据集,同时引入邻域特征以应对晶片加工过程中动态因素对材料去除率的影响。提出基于深度自动编码器的多源数据融合及材料去除率预测方法。设计深度自动编码器参数,优化深度自动编码器的损失函数从而增强深度自动编码器对强相关性特征变量的重建。基于深度自动编码器进行多源传感器信号融合,降低数据维度。使用超参数搜索算法优化BP神经网络超参数,利用BP神经网络方法将融合后的数据进行半导体晶片抛光过程中的材料去除率预测。结果 采用PHM2016数据集对模型进行验证,均方误差MSE达到7.862,相关性R²达到91.2%。结论 基于多源数据的融合模型能有效预测MRR,可以对半导体晶片CMP工艺过程的智能决策与控制起到良好的辅助作用。     

SVR-PSO算法在慢走丝线切割参数优化中的应用

针对慢走丝线切割加工中难以同时获得较快加工速度和较优表面质量的问题,从其加工参数与加工指标之间的高非线性关系入手,选取水压、脉冲时间、脉冲宽度、峰值电流和进给速率作为优化参数,以表面粗糙度(Ra)、材料去除率(MRR)作为优化指标,设计正交实验;创新运用支持向量机(SVR)结合粒子群算法(PSO)建立其多目标预测优化模型,得到最优加工参数。结果表明:所建立的多目标预测优化模型优化效果十分显著,相同Ra下MRR平均提高32%;相同MRR下Ra同比下降25%。     

金刚石木工刀具材料蚀除量的灰色组合预测模型

本文在多变量灰色组合预测模型的建模基础上,以金刚石木工刀具电火花磨削工艺参数正交设计实验结果作为数据样本,建立了金刚石木工刀具材料蚀除量的预测模型,该模型为多元线性回归模型的一种改进模型。本文以电火花磨削工艺参数作为输入量,以蚀除量作为输出量,结合实验数据进行了金刚石木工刀具材料蚀除量预测模型的验证,结果表明所建立的预测模型能够较好地预测出金刚石木工刀具的材料蚀除量。     

超声波加工工艺的材料去除率建模及试验研究

对硬脆材料的超声波加工工艺进行了研究,分析了材料去除机理,建立了材料去除率数学模型,给出了材料去除率与各工艺参数之间的关系。通过对玻璃进行超声波加工试验,进一步验证了该模型的正确性。     

砂带磨削表面粗糙度理论预测及灵敏度分析

目的 以钢化玻璃磨边为研究对象,建立金刚石砂带磨削表面粗糙度理论预测模型,并分析粗糙度对各工艺因素的灵敏度。方法 首先,采用多因素线性回归分析建立了关于磨削工艺参数的粗糙度理论预测模型;其次,通过正交试验研究了磨削压力、砂带线速度和砂带张紧力对粗糙度和材料去除率的影响大小,并得到了工艺参数的优水平组合;再次,根据正交试验结果计算了粗糙度理论预测模型的数学表达式,同时,建立了灵敏度模型来进行工艺因素的灵敏度分析和工艺参数的区间优化;最后,利用随机试验验证了粗糙度理论预测模型的准确性。结果 极差分析可知,RA（0.137）?RC（0.068）?RB（0.016）,MC（6.828）?MA（5.228）?MB（1.784）,磨削工艺参数的优水平组合为A2B3C3。电镀金刚石砂带磨削表面粗糙度理论预测模型的表达式为 。各工艺参数的优选区间为：磨削压力10~20 N,线速度15~30 m/s,张紧力40~60 N。随机试验可得,粗糙度理论预测模型的相对误差大小维持在5.5%~10%。结论 关于工艺因素对磨削质量的影响,磨削压力最大,砂带张紧力次之,砂带线速度最小。关于工艺因素对材料去除率的影响,砂带张紧力最大,磨削压力次之,砂带线速度最小。磨削压力为18 N、砂带线速度为30 m/s、砂带张紧力为55 N时,磨削表面质量最好,且材料去除率较高。试验参数范围内,粗糙度对磨削压力的灵敏度随磨削压力的增加而下降,对砂带线速度和砂带张紧力的灵敏度随着二者的增加而增加。15组随机试验表明,粗糙度理论预测模型具有较高的可靠性和准确性。     

五轴联动铣削复杂曲面表面粗糙度研究

为了提高五轴联动铣削复杂曲面的加工质量,分析多切削工艺参数对表面粗糙度的影响至关重要。首先,通过单因素实验分析了各切削工艺参数对表面粗糙度的影响规律,基于模拟退火算法理论,分别建立了各切削工艺参数与表面粗糙度的一元关系模型;其次,通过对单因素实验数据进行归一化处理,为正交实验优选切削工艺参数区间;最后,通过正交实验,分别建立了基于模拟退火及传统最小二乘原理的表面粗糙度多元复合预测模型并通过实验进行验证。验证结果表明,所建立的预测模型能够为复杂曲面铣削加工优选加工参数提供更准确的指导。     

不同电极材料的短电弧铣削加工效率研究

短电弧铣削加工是一种新型的放电加工,它进一步提高了放电加工效率。论述了短电弧加工材料去除机制、去离子原则和热现象,分析了余热对材料去除率(MRR)的影响。研究了短电弧铣削加工效率的主要指标——MRR,在不同工具、工件电极的材料组合下,分析峰值电流、脉冲时间、脉冲间隔、进给速度、气压等工艺因素对MRR的影响规律。实验表明:不同电极材料组合的MRR存在差异;在大多数放电条件下,石墨电极和45碳钢工件获得较高的MRR,而紫铜电极和镍基高温合金GH4169工件获得较低的MRR。     

基于SPSO–BP神经网络的自适应抛光工艺参数匹配

目的 在湿性物理抛光作业中,根据不同工件的表面抛光质量和效率要求,实现抛光工艺参数的自适应匹配,达到理想的抛光效果。方法 基于工件表面材料去除原理,建立工艺参数与材料去除率(MRR)和表面粗糙度的数学关系模型,明确影响抛光效果的工艺参数。针对工艺参数与抛光质量和效率之间的复杂且交互影响的关系,以及理论计算的抛光效果与实际结果存在差异的问题,提出SPSO–BP预测模型,分别以20组不同的抛光工艺参数与对应抛光结果为训练样本,训练SPSO–BP模型,并与传统PSO–BP模型进行对比。基于训练好的预测模型,根据不同的基础条件与抛光质量和抛光效率的要求,通过模型自适应匹配抛光工艺参数。针对SUS304板材,设定表面粗糙度目标R_a1—R_a5和材料去除率目标R_m1—R_m5,分别通过SPSO–BP和PSO–BP模型预测获得的工艺参数进行抛光试验,将获得的真实粗糙度Ra_z1—Ra_z5和材料去除率R_mz1—R_mz5与目标值进行对比...     

Development of empirical model for different process parameters during rotary electrical discharge machining of copper–steel (EN-8) system

The present work investigates the machining characteristics of EN-8 steel with copper as a tool electrode during rotary electrical discharge machining process. The empirical models for prediction of output parameters have been developed using linear regression analysis by applying logarithmic data transformation of non-linear equation. Three independent input parameters of the model viz. peak current, pulse on time and rotational speed of tool electrode are chosen as variables for evaluating the output parameters such as metal removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). Analysis of the results, by using Taguchi's recommended signal–noise ratio formulae and ANOVA, has been conducted to identify the significant parameters and their degree of contribution in the process output. Analyzed results shows that peak current and pulse on time are the most significant and significant parameters for MRR and EWR, respectively. But peak current and electrode rotation become the most significant and significant parameters for SR, respectively. Experimental results further revealed that maximizing the MRR while minimizing EWR and improving the surface roughness, cannot be achieved simultaneously at a particular combination of control parameters setting. In addition, the predictions based on the above developed models have been verified with another set of experiments and are found to be in good agreement with the experimental results.     

Investigation of the spark cycle on material removal rate in wire electrical discharge machining of advanced materials

The development of new, advanced engineering materials and the need for precise and flexible prototypes and low-volume production have made the wire electrical discharge machining (EDM) an important manufacturing process to meet such demands. This research investigates the effect of spark on-time duration and spark on-time ratio, two important EDM process parameters, on the material removal rate (MRR) and surface integrity of four types of advanced material: porous metal foams, metal bond diamond grinding wheels, sintered Nd-Fe-B magnets, and carbon–carbon bipolar plates. An experimental procedure was developed. During the wire EDM, five types of constraints on the MRR due to short circuit, wire breakage, machine slide speed limit, and spark on-time upper and lower limits are identified. An envelope of feasible EDM process parameters is generated for each work-material. Applications of such a process envelope to select process parameters for maximum MRR and for machining of micro features are discussed. Results of Scanning Electron Microscopy (SEM) analysis of surface integrity are presented.     

Experimental investigation on the influence of electrochemical machining parameters on machining rate and accuracy in micromachining domain

Non-conventional machining is increasing in importance due to some of the specific advantages which can be exploited during micromachining operation. Electrochemical micromachining (EMM) appears to be a promising technique, since in many areas of application, it offers several special advantages that include higher machining rate, better precision and control, and a wider range of materials that can be machined. A better understanding of high rate anodic dissolution is urgently required for EMM to become a widely employed manufacturing process in the micro-manufacturing domain. An attempt has been made to develop an EMM experimental set-up for carrying out in depth research for achieving a satisfactory control of the EMM process parameters to meet the micromachining requirements. Keeping in view these requirements, sets of experiments have been carried out to investigate the influence of some of the predominant electrochemical process parameters such as machining voltage, electrolyte concentration, pulse on time and frequency of pulsed power supply on the material removal rate (MRR) and accuracy to fulfil the effective utilization of electrochemical machining system for micromachining. A machining voltage range of 6 to 10 V gives an appreciable amount of MRR at moderate accuracy. According to the present investigation, the most effective zone of pulse on time and electrolyte concentration can be considered as 10–15 ms and 15–20 g/l, respectively, which gives an appreciable amount of MRR as well as lesser overcut. From the SEM micrographs of the machined jobs, it may be observed that a lower value of electrolyte concentration with higher machining voltage and moderate value of pulse on time will produce a more accurate shape with less overcut at moderate MRR. Micro-sparks occurring during micromachining operation causes uncontrolled material removal which results in improper shape and low accuracy. The present experimental investigation and analysis fulfils various requirements of micromachining and the effective utilization of ECM in the micromachining domain will be further strengthened.     

On Electro Discharge Machining of Inconel 718 with Hollow Tool

Inconel 718 is a nickel-based alloy designed for high yield, tensile, and creep-rupture properties. This alloy has been widely used in jet engines and high-speed airframe parts in aeronautic application. In this study, electric discharge machining (EDM) process was used for machining commercially available Inconel 718. A copper electrode with 99.9% purity having tubular cross section was employed to machine holes of 20?mm height and 12?mm diameter on Inconel 718 workpieces. Experiments were planned using response surface methodology (RSM). Effects of five major process parameters??pulse current, duty factor, sensitivity control, gap control, and flushing pressure on the process responses??material removal rate (MRR) and surface roughness (SR) have been discussed. Mathematical models for MRR and SR have been developed using analysis of variance. Influences of process parameters on tool wear and tool geometry have been presented with the help of scanning electron microscope (SEM) micrographs. Analysis shows significant interaction effect of pulse current and duty factor on MRR yielding a wide range from 14.4 to 22.6?mm³/min, while pulse current remains the most contributing factor with approximate changes in the MRR and SR of 48 and 37%, respectively, corresponding to the extreme values considered. Interactions of duty factor and flushing pressure yield a minimum surface roughness of 6.2???m. The thickness of the sputtered layer and the crack length were found to be functions of pulse current. The hollow tool gets worn out on both the outer and the inner edges owing to spark erosion as well as abrasion due to flow of debris.     

Pulse train data analysis to investigate the effect of machining parameters on the performance of wire electro discharge turning (WEDT) process

This paper aims at giving an insight into the wire electro discharge turning (WEDT) process, by analyzing the effect of machining parameters on material removal rate (MRR), surface roughness and roundness error, using the pulse train data acquired at the spark gap. To achieve this objective a simple and cost effective spindle is developed for the WEDT process. Pulse train data are acquired with a data acquisition system developed in the present work. A pulse discrimination algorithm has been developed for classifying the discharge pulses into open circuit, normal, arc and short circuit pulses. With the help of algorithm the number of arc regions, average ignition delay time, the width of the normal and arc regions in the data acquired can also be obtained. It has been observed that the rotation of the workpiece has significant influence on the type of the discharges occurring at the spark gap. Preliminary experiments conducted to compare the WEDM and WEDT processes disclosed that MRR is less in WEDT and the number of arcs and arc regions are more in WEDT. It has been observed that the surface roughness and roundness error of the WEDT components are influenced by the occurrence of arc regions, width of arc and normal discharge regions and average ignition delay time.     

导丝器对中走丝电火花线切割加工工艺的影响

目前中走丝电火花线切割机床加工过程大多是在上线架与下线架之间放置工件进行加工,而为了获得较高的加工精度和表面粗糙度就要进行多次切割。传统中走丝线切割机床在进行加工时,会由于钼丝抖动对加工工件产生影响。通过对比加装导丝器后进行单次切割和多次切割实验,探究机床加装导丝器后对工件加工的影响,及导丝器进行长时间加工后是否会造成较大磨损导致加工零件尺寸精度出现变化。实验采取单因素变量,脉冲宽度、脉冲间隔、脉宽/脉间、峰值电流和走丝速度等电参数均设置相同。     

TiNi形状记忆合金的电火花加工性能

TiNi形状记忆合金由于具有优异的超弹性和形状记忆效应等性能而被大量地应用于工业生产中。然而,形状记忆合金的传统加工相当复杂。因此,研究TiNi形状记忆合金的电火花线切割加工（WEDM）性能。采用L27正交阵列以尽量减少实验。在不同的脉冲持续时间、脉冲关断时间、伺服电压、冲洗压力和线速度条件下进行实验。为同步优化提出一种利用Taguchi设计与实用理念的多响应优化方法。通过对信噪比（S/N）的均值分析和方差分析,确定最佳参数水平。Taguchi分析表明：1μs脉冲持续时间、3.8μs脉冲关断时间、40 V伺服电压、1.8×105Pa冲洗压强和8 m/min线速度,有利于同时使材料去除率最大化和表面粗糙度最小化。TiNi形状记忆合金电火花线切割加工的优化结果表明：脉冲持续时间显著影响材料去除率和表面粗糙度。在较长的脉冲持续时间时,在加工表面可观察到放电坑、微裂纹和重铸层。     

Fundamental geometry analysis of wire electrical discharge machining in corner cutting

Fundamental geometry properties of wire electrical discharge machining (WEDM) process in corner cutting is studied. The concept of discharge-angle is introduced, and its mathematical expression is derived by analytical geometry. A model to estimate the metal removal rate (MRR) in geometrical cutting is developed by considering wire deflection with transformed exponential trajectory of wire centre. The computed MRR is compared with measured sparking frequency of the process since they are equivalent to each other for an iso-energy type machine. A very good agreement is obtained. Both of the discharge-angle and MRR drop drastically to a minimum value depending on the corner angle being cut as the guides arrive at the corner apex, and then recover to the same level of straight-path cutting sluggishly. Hence the observed phenomenon of increased gap-voltage and decreased sparking frequency in corner cutting can be physically interpreted. In addition, the variation of the machining load caused by the change of MRR, which was taken as unknown disturbance in the past, can be predicted and used for control purpose.     

Modeling of material removal rate in electric discharge grinding process

The mechanism of material removal in electric discharge grinding (EDG) is very complex due to interdependence of mechanical and thermal energies responsible for material removal. Therefore, on the basis of conceived process physics for material removal, an attempt has been made to predict the material removal rate (MRR). The proposed mathematical model is based on the fundamental principles of material removal in electric discharge machining (EDM) and conventional grinding processes. The inter-dependence of the thermal and mechanical phenomena has been realized by scanning electron microscopy (SEM) characterization of the samples machined at different processing conditions. The key input process parameters like pulse on time, pulse current, gap voltage, duty cycle, pulse off time, frequency, depth of cut, wheel speed and table speed are co-related with MRR for three distinct idealized processing conditions. The constant showing the extent of interdependence of two phenomena were evaluated by experimental data. The obtained expressions of MRR have been validated for processing conditions other than those used for obtaining constants. It was found that the discharge energy plays prominent role in material removal. The percentage difference in experimental findings and theoretical predictions was found to be less than 3%.