Dynamic characterization of machining systems

In the working space model of machining, an experimental procedure is implemented to determine the elastic behaviour of the machining system. In this paper, a dynamic characterization and vibration analysis has long been used for the detection and identification of the machine tool condition. The natural frequencies of the lathe machining system are required (Ernault HN400??France) according to three different situations with no cutting process are acquired. The system modal analysis is used to identify the natural frequencies. These frequencies are then compared to the ones obtained on the spindle numerical model by finite element method. This work is validated by experimental tests based on measures of the lathe machine tool frequencies domain. The main objective is to identify a procedure giving the natural frequency values for the machine tool components, in order to establish a better condition in the cutting process of the machine tool.     

基于特征的刀具“形-性-用”一体化设计方法

刀具作为机床的"牙齿",在金属切削中非常重要,目前专用化是刀具发展的一个主要趋势,挑战刀具设计的灵活性和准确性。为了实现这一目标,提出了刀具"形-性-用"一体化设计方法,它以加工需求为驱动,利用切削过程中涉及的理论(几何约束、切削力作用、切削层作用机理、刀具强度理论、高温材料学属性以及化学反应关系等),并通过刀具设计特征,将刀具的形状、性能和使用结合起来,进而实现针对加工需求的专用刀具设计,以及相应的加工条件和切削参数等的确定。然后建立了刀具"形-性-用"一体化设计方法系统框架,并开发了其软件平台。最后采用示例分析,展示本方法的刀具参数优化过程和刀具建模过程,进而证明本方法的可行性。刀具"形-性-用"一体化设计方法为刀具专用化发展提供一种新方法和新思路。     

Cutting heat dissipation in high-speed machining of carbon steel based on the calorimetric method

The cutting heat dissipation in chips, workpiece, tool and surroundings during the high-speed machining of carbon steel is quantitatively investigated based on the calorimetric method. Water is used as the medium to absorb the cutting heat; a self-designed container suitable for the high-speed lathe is used to collect the chips, and two other containers are adopted to absorb the cutting heat dissipated in the workpiece and tool, respectively. The temperature variations of the water, chips, workpiece, tool and surroundings during the closed high-speed machining are then measured. Thus, the cutting heat dissipated in each component of the cutting system, total cutting heat and heat flux are calculated. Moreover, the power resulting from the main cutting force is obtained according to the measured cutting force and predetermined cutting speed. The accuracy of cutting heat measurement by the calorimetric method is finally evaluated by comparing the total cutting heat flux with the power resulting from the main cutting force.     

基于人工神经网络的变切削条件下钻头磨损监控

基于人工神经网络变切削条件下的钻头磨损监控系统，以机床主轴和进给轴的电机功率（电流）信号的为监控信号，并通过机床的速度向量识别机床的加工状态；通用对监控信号的提取和预处理，得到人工神经网络模型的输入（有效切削功率和切削用量）用３层ＢＰ网络对钻头的磨损量进行预报。     

Experimental investigation of machining characteristics and chatter stability for Hastelloy-X with ultrasonic and hot turning

Ultrasonic-assisted machining is a machining operation based on the intermittent cutting of material which is obtained through vibrations generated by an ultrasonic system. This method utilizes low-amplitude vibrations with high frequency to prevent continuous contact between a cutting tool and a workpiece. Hot machining is another method for machining materials which are difficult to cut. The basic principle of this method is that the surface of the workpiece is heated to a specific temperature below the recrystallization temperature of the material. This heating operation can be applied before or during the machining process. Both of these operations improve machining operations in terms of workpiece-cutting tool characteristics. In this study, a novel hybrid machining method called hot ultrasonic-assisted turning (HUAT) is proposed for the machinability of Hastelloy-X material. This new technique combines ultrasonic-assisted turning (UAT) and hot turning methods to take advantage of both machining methods in terms of machining characteristics, such as surface roughness, stable cutting depths, and cutting tool temperature. In order to observe the effect of the HUAT method, Hastelloy-X alloy was selected as the workpiece. Experiments on conventional turning (CT), UAT, and HUAT operations were carried out for Hastelloy-X alloy, changing the cutting speed and cutting tool overhang lengths. Chip morphology was also observed. In addition, modal and sound tests were performed to investigate the modal and stability characteristics of the machining. The analysis of variance (ANOVA) method was performed to find the effect of the cutting speed, tool overhang length, and machining techniques (CT, UAT, HUAT) on surface roughness, stable cutting depths, and cutting tool temperature. The results show both ultrasonic vibration and heat improve the machining of Hastelloy-X. A decrease in surface roughness and an increase in stable cutting depths were observed, and higher cutting tool temperatures were obtained in UAT and HUAT compared to CT. According to the ANOVA results, tool overhang length, cutting speed, and machining techniques were effective parameters for surface roughness and stable cutting depths at a 1% significance level (p ≤ 0.01). In addition, cutting speed and machining techniques have an influence on cutting tool temperature at a 1% significance level (p ≤ 0.01). During chip analysis, serrated chips were observed in UAT and HUAT.     

硬质合金孔加工刀具的技术进展

简要介绍了现代制造技术中常用孔加工刀具的种类、硬质合金刀具的材料与制备.以钻头为例,分析了刀具参数、刃磨、刃口钝化技术对切削性能的影响,综述了硬质合金孔加工刀具技术的发展趋势.     

Development of in situ system to monitor the machining process using a piezo load cell

The measurement of cutting force is one of the most frequently used techniques for monitoring machining processes. Its widespread application ranges from tool condition identification, feedback control and cutting system design to process optimization.This paper suggests another system for measuring cutting force in milling processes. Generally, tool dynamometers are taken into account for the most appropriate cutting force measuring tool in the analysis of a cutting mechanism. However, high prices and limited working space make in situ systems difficult for a controllable milling process. Although an alternative suggestion is to use an AC current from a servomotor, it is unsuitable for cutting force monitoring because of a small upper frequency limit and noise.The suggested cutting force measuring system is composed of two piezo load cells placed between the moving table bracket and the nut flange of the ball screw. It has many advantages, such as lower cost and a wider measurement range than the tool dynamometer, over using the built-in feeding system and the low-cost piezo load cell for applying a conventional machining center.This paper focuses on the performance test of a newly developed measuring system. By comparing the cutting force between the tool dynamometer and the system developed from a series of end milling experiments, the accuracy of the cutting force measurement system was verified. Linearity, transverse sensitivity and the upper frequency limit of the system were verified by experiment.     

Modeling and Optimization of Machining Process in Discontinuously Reinforced Aluminium Matrix Composites

This article presents development of an Artificial Neural Networks (ANN) based model for the prediction of surface roughness during machining of composite material using Back Propagation algorithm. Statistically designed experiments based on Taguchi method were carried out on machining of Al/SiCp composite material. The experimentation helped generate a knowledge base for the ANN system and understand the relative importance of process, tool and work material dependent parameters on the roughness of surface generated during machining. The ANN model trained using the experimental data was found to predict the surface roughness with fair accuracy. An optimization approach was also proposed to obtain optimal cutting conditions that yield the desired surface roughness while maximizing the metal removal rate.     

难加工材料枪钻加工技术研究

深孔加工是机械加工领域的重要分支,在钛合金、沉淀硬化不锈钢等难加工材料的深孔加工过程中,存在加工表面质量差、刀具崩刃、磨损严重和断屑排屑困难等问题。枪钻是深孔加工领域发展最早、应用范围最广的深孔加工刀具之一,其几何结构特殊,在深孔加工中具有加工质量好、效率高、直线度好等特点。本文介绍了枪钻的主要结构及受力情况,分析了枪钻的切削加工过程及其断屑条件,通过对切屑、切削力和切削温度的研究,得到了刀具、工艺参数以及切屑对加工质量和刀具磨损的影响规律。最后以两种典型的难加工材料为代表,分析了难加工材料深孔加工的特点。研究结果对难加工材料的枪钻深孔加工具有重要的指导意义。     

HIGH THROUGHPUT DRILLING OF TITANIUM ALLOYS

The experiments of high throughput drilling of Ti-6Al-4V at 183 m/min cutting speed and 156 mm3/s material removal rate using a 4 mm diameter WC-Co spiral point drill are conducted. At this material removal rate, it took only 0.57 s to drill a hole in a 6.35 mm thick Ti plate. Supplying the cutting fluid via through-the-drill holes and the balance of cutting speed and feed have proven to be critical for drill life. An inverse heat transfer model is developed to predict the heat flux and the drill temperature distribution in drilling. A three-dimensional finite element modeling of drilling is con-ducted to predict the thrust force and torque. Experimental result demonstrates that, using proper machining process parameters, tool geometry, and fine-grained WC-Co tool material, the high throughput machining of Ti alloy is technically feasible.     

Artificial neural network based tool condition monitoring in micro mechanical peck drilling using thrust force signals

Micro scale machining process monitoring is one of the key issues in highly precision manufacturing. Monitoring of machining operation not only reduces the need of expert operators but also reduces the chances of unexpected tool breakage which may damage the work piece. In the present study, the tool wear of the micro drill and thrust force have been studied during the peck drilling operation of AISI P20 tool steel workpiece. Variations of tool wear with drilled hole number at different cutting conditions were investigated. Similarly, the variations of thrust force during different steps of peck drilling were investigated with the increasing number of holes at different feed and cutting speed values. Artificial neural network (ANN) model was developed to fuse thrust force, cutting speed, spindle speed and feed parameters to predict the drilled hole number. It has been shown that the error of hole number prediction using a neural network model is less than that using a regression model. The prediction of drilled hole number for new test data using ANN model is also in good agreement to experimentally obtained drilled hole number.     

Real-time cutting tool state recognition approach based on machining features in NC machining process of complex structural parts

Cutting tool state recognition plays an important role in ensuring the quality and efficiency of NC machining of complex structural parts, and it is quite especial and challengeable for complex structural parts with single-piece or small-batch production. In order to address this issue, this paper presents a real-time recognition approach of cutting tool state based on machining features. The sensitive parameters of monitored cutting force signals for different machining features are automatically extracted, and are associated with machining features in real time. A K-Means clustering algorithm is used to automatically classify the cutting tool states based on machining features, where the sensitive parameters of the monitoring signals together with the geometric and process information of machining features are used to construct the input vector of the K-Means clustering model. The experiment results show that the accuracy of the approach is above 95% and the approach can solve the real-time recognition of cutting tool states for complex structural parts with single-piece and small-batch production.     

面向加工特征的刀具和切削参数计算机辅助选择系统

切削刀具制造商面临围绕大量工件材料和加工特征为客户提供合理刀具和切削参数的现状,切削工艺规划的核心步骤也是刀具和切削参数的确定。确定刀具和切削参数一般多从零件材料角度出发,可能导致工件与刀具不匹配。文中提出面向加工特征的刀具和切削参数计算机辅助选择系统的开发。系统包括车削特征、铣削特征、钻削和镗削加工特征,系统利用特征图形作为用户交互式接口,采用关系数据库结合数据驱动和规则推理逻辑来选择刀具和切削参数,利用数学模型计算过程参数包括单工步加工工时、切削功率、最大粗糙度等,并辅助制定工序。以车刀和车削参数选择为例,介绍该系统的实现方法。该系统可以辅助设计师及工艺人员选择合理的刀具和切削参数。     

Investigation of diamond cutting tool lapping system based on on-machine image measurement

The profile tolerance of diamond cutting tool??s edge is one of the key factors in affecting machining accuracy. With the development of ultra-precision machining technology for optical free-form surfaces and optical microstructures, the demand for high-precision round nose diamond cutting tools is increasing. In this study, an on-machine image processing approach is applied to cutting edge geometry truing process, and profile data of cutting edge in sub-pixel precision is acquired using a series of image processing methods. According to the profile captured, the deviation from an ideal cutting edge is calculated and feedbacked to the controller. The lapping system is employed to lap the cutting edge pertinently using the deviation and the corresponding position captured, and the round edge of high accuracy is obtained efficiently. This method can avoid the error caused by the process of refixturing for offline measurement in the traditional lapping method of diamond cutting tool and reduce the influence of human factors. A truing experiment for cutting edge of the monocrystal diamond cutting tool is carried out at the developed lapping system based on on-machine image measurement, and round cutting edge of profile tolerance less than or equal to ±0.5???m is achieved.     

基于有限元数值模型和进给速度优化的薄壁件侧铣变形在线控制

为实现在加工过程中对薄壁件侧铣产生的较大切削变形进行在线控制,提出基于有限元数值模型和进给速度优化的在线控制策略。根据薄壁件切削过程的有限元仿真结果,建立数控机床进给速度、切削力、工件切削变形间的数值模型,进而确定用于控制变形的最优目标切削力。在具有开放式模块化的数控系统平台上开发了切削力信号实时采集、滤波功能和基于Brent-Dekker算法的进给速度在线优化策略,并根据滤波后的切削力及相应算法在加工过程中实时调整机床进给速度,保证切削力逐渐接近最优控制目标而实现切削变形的在线控制。试验结果表明,经过进给速度在线优化后的切削过程可将薄壁件侧铣变形控制在规定范围内,同时提高了切削效率。     

Self-sensing of cutting forces in diamond cutting by utilizing a voice coil motor-driven fast tool servo

Cutting force measurement is important for monitoring the diamond cutting process. In this paper, a new measurement method of thrust cutting force associated with a voice coil motor (VCM) driven fast tool servo (FTS) system has been developed. Instead of integrating additional force sensors to the FTS which would influence the dynamics of the FTS, the force measurement in the proposed system is achieved associated with in-process monitoring the variation of the driving current of the VCM and pre-process determining the system parameters. In this way, the cutting forces are accurately obtained by subtracting the influences of the driving force, the spring force, the damping force and the inertial force associated with the system as well as the cutting process. Based on the proposed method, a microstructure array was machined using the developed VCM-FTS and the cutting force during the machining process was monitored in real time. The measured force signal was in good agreement with the machining result. The surface profile error of the fabricated microstructure could be clearly distinguished by the variation of the measured cutting force signal. This provides a new approach for in-process cutting force measurement associated with FTS based diamond cutting process.     

复杂曲面模具加工系统综合刚度场建模与分析*

在加工汽车覆盖件模具复杂曲面时,机床-刀具刚度、刀具位姿变化、模具型面变化都会影响加工系统综合刚度,进而影响模具加工精度。以四轴数控加工中心为例,针对模具曲面特征设置相应采样点,依据多体小变形理论,通过点传递矩阵、雅可比矩阵等完成该采样点的加工系统综合刚度建模,并引入了力椭球。在刀具不同的空间姿态下,通过力椭球分析了机床横梁、刀柄、刀具、模具曲面特征等对加工系统综合刚度性能的影响,揭示了曲面模具加工系统综合刚度的分布规律。最后通过试验证明,该理论模型可以有效地优化复杂型面模具加工工艺,减小模具的加工误差。     

Modeling and Optimization of Machining Process in Discontinuously Reinforced Aluminium Matrix Composites

Abstract

This article presents development of an Artificial Neural Networks (ANN) based model for the prediction of surface roughness during machining of composite material using Back Propagation algorithm. Statistically designed experiments based on Taguchi method were carried out on machining of Al/SiCp composite material. The experimentation helped generate a knowledge base for the ANN system and understand the relative importance of process, tool and work material dependent parameters on the roughness of surface generated during machining. The ANN model trained using the experimental data was found to predict the surface roughness with fair accuracy. An optimization approach was also proposed to obtain optimal cutting conditions that yield the desired surface roughness while maximizing the metal removal rate.     

基于样本聚类模糊神经网络的刀具磨损状态实时识别

利用一种根据K－means方法对样本聚类后建立的改进模型神经网络（MTFNN）模型,对刀具后刀面磨损量进行在线工况实时识别。仿真结果表明该工况辨识模型精度高,收敛速度快,实用性较强,适宜于复杂的,非线性加工系统建模。     

Characteristic investigation of pipe cutting technology based on electro-discharge machining

Pipe cutting technology plays an important role in the process of offshore platforms decommissioning, as many devices such as tubing, drill pipe, and casing need to be decommissioned. In this study, a novel cutting pipe technology based on electro-discharge machining (EDM) is proposed, and a cutting pipe mechanism is developed to cut the pipes for decommissioning offshore platforms. The machining principles and characteristics of the technique are described. The effects of machining parameters, including tool polarity, dielectric fluid, electrode material and width, pulse on-time, pulse off-time, peak voltage, and electrode rotation speed to machining performance, are investigated. The material removal rate (MRR) of the machined casing and tool electrode wear ratio (EWR) is obtained based on the calculation of the percentage of mass loss per machining time. The experimental results show that a better cutting performance can be obtained with negative tool polarity at the conditions of dielectric fluid of emulsion, pulse on-time of 500 μs, pulse off-time of 200 μs, peak voltage of 70 V, copper electrode width of 28 mm, and electrode rotation speed of 250 rpm is a better choice. Additionally, the cutting slots surface has been investigated by the means of SEM. The cutting slots machined by the rotary EDM are clean and smooth.