正交车铣TC4钛合金表面粗糙度分析

车铣加工技术是近年发展起来的先进切削加工技术之一。本文采用多因素正交试验法,进行了一系列的正交车铣TC4钛合金切削试验,研究了车铣切削用量与表面粗糙度之间的变化规律。通过方差分析确定了各因素对表面粗糙度的影响大小的主次顺序,每齿进给量和偏心量对表面粗糙度的影响较大。采用回归分析原理,建立了表面粗糙度的预测模型,根据统计检验结果表明,已加工表面粗糙度预测模型呈高度显著检验状态,具有很高的可信度。     

高速铣削超高强度钢的切削力及表面粗糙度研究

选用涂层硬质合金刀具对300M超高强度钢进行高速铣削试验,通过单因素试验和多因素正交试验法,得出铣削参数(主轴转速、每齿进给量、铣削深度)对切削力及表面粗糙度的影响规律及主次关系。对正交试验结果做最小二乘法分析,建立切削力及表面粗糙度与铣削参数之间的经验模型;对经验模型的回归方程及系数做显著性检验,并对其进行参数优化,得出铣削参数的最优组合。结果表明:主轴转速和铣削深度对切削力的作用较大,而每齿进给量对其影响相对较弱;每齿进给量对表面粗糙度作用最强,铣削深度次之,主轴转速对其作用最弱。     

Empirical models and optimal cutting parameters for cutting forces and surface roughness in hard milling of AISI H13 steel

In the present research, an attempt has been made to experimentally investigate the effects of cutting parameters on cutting forces and surface roughness in hard milling of AISI H13 steel with coated carbide tools. Based on Taguchi’s method, four-factor (cutting speed, feed, radial depth of cut, and axial depth of cut) four-level orthogonal experiments were employed. Three cutting force components and roughness of machined surface were measured, and then range analysis and analysis of variance (ANOVA) are performed. It is found that the axial depth of cut and the feed are the two dominant factors affecting the cutting forces. The optimal cutting parameters for minimal cutting forces and surface roughness in the range of this experiment under these experimental conditions are searched. Two empirical models for cutting forces and surface roughness are established, and ANOVA indicates that a linear model best fits the variation of cutting forces while a quadratic model best describes the variation of surface roughness. Surface roughness under some cutting parameters is less than 0.25 μm, which shows that finish hard milling is an alternative to grinding process in die and mold industry.     

TC17钛合金低温铣削表面粗糙度预测

进行了TC17钛合金低温铣削试验,研究了不同切削条件下的已加工表面粗糙度.采用回归分析方法建立了表面粗糙度经验模型,研究了射流温度、每齿进给量、铣削速度和径向切削深度对表面粗糙度的影响规律.基于BP神经网络建立了表面粗糙度预测模型,并与经验模型进行了对比分析.研究结果表明,基于经验模型表面粗糙度值与参数间存在强相关性(...     

基于ELMAN网络的高速平面铣削表面粗糙度的研究

本文使用人工神经网络方法建立了高速平面铣削条件下切削参数对加工表面粗糙度影响的模型。通过高速切削实验，利用正交试验组合数据组训练神经网络。研究和预测切削速度、切削深度和每齿进给量对加工表面粗糙度的影响，通过实测数据测试了模型的性能，取得了较好的效果，该方法可以用于预测高速平面铣削表面粗糙度。     

Surface topography and roughness of high-speed milled AlMn1Cu

The aluminum alloy AlMn1Cu has been broadly applied for functional parts production because of its good properties. But few researches about the machining mechanism and the surface roughness were reported. The high-speed milling experiments are carried out in order to improve the machining quality and reveal the machining mechanism. The typical topography features of machined surface are observed by scan electron microscope(SEM). The results show that the milled surface topography is mainly characterized by the plastic shearing deformation surface and material piling zone. The material flows plastically along the end cutting edge of the flat-end milling tool and meanwhile is extruded by the end cutting edge, resulting in that materials partly adhere to the machined surface and form the material piling zone. As the depth of cut and the feed per tooth increase, the plastic flow of materials is strengthened and the machined surface becomes rougher. However, as the cutting speed increases, the plastic flow of materials is weakened and the milled surface becomes smoother. The cutting parameters (e.g. cutting speed, feed per tooth and depth of cut) influencing the surface roughness are analyzed. It can be concluded that the roughness of the machined surface formed by the end cutting edge is less than that by the cylindrical cutting edge when a cylindrical flat-end mill tool is used for milling. The proposed research provides the typical topography features of machined surface of the anti-rust aluminum alloy AlMn1Cu in high speed milling.     

Ultrasonic vibration-assisted milling of aluminum alloy

The objective of this paper is to investigate the effects of assisted ultrasonic vibration in the operation of micro end milling. Based upon numerical analysis for the trajectory of a tool tip of a two-flute end mill, it was found that the assisted feed direction ultrasonic vibration can achieve separate-type milling that is different from conventional operation by reasonable parameter matching. To validate theoretical analysis and investigate the influence of ultrasonic vibration on milling process, a slot-milling experiment was conducted on an aluminum alloy work piece. The desired ultrasonic vibration was applied in the feed direction by an ultrasonic vibrator. Through investigating and comparing some experimental results involving cutting force, chip formation, surface topography, surface roughness, and machining dimensional accuracy, the authors found that micro end milling with ultrasonic vibration in the feed direction leads to a pulse-like cutting force and produces uniform small chips. Assisted ultrasonic vibration in the feed direction has a negative effect on the surface roughness of the slot bottom, but a positive effect on the dimensional accuracy of the slot width.     

基于响应曲面法的表面粗糙度预测模型的建立与切削参数的优选

文中通过试验设计的方法研究了高速精加工中切削参数的选择对表面粗糙度的影响.采用响应曲面法建立表面粗糙度的响应模型,分析了切削速度、进给量、背吃刀量对表面粗糙度的影响以及切削参数的优选.结果显示背吃刀量对表面粗糙度的影响最为显著,进给量次之,切削速度影响最小.在表面粗糙度选定的情况下,优先选择背吃刀量可以提高加工效率.     

基于回归分析方法的铣削表面粗糙度预测模型的建立

依据正交试验结果,利用回归分析方法建立了高速钢球头铣刀铣削铝合金工件时表面粗糙度的预测模型,并对该模型的回归方程和系数进行了显著性检验.该模型对预报表面粗糙度具有高度显著性:切削深度和走刀行距对表面粗糙度的影响显著,而主轴转速和每齿进给量对表面粗糙度影响不显著.     

A study of Taguchi optimization method for identifying optimum surface roughness in CNC face milling of cobalt-based alloy (stellite 6)

The aim of this work is to develop a study of Taguchi optimization method for low surface roughness value in terms of cutting parameters when face milling of the cobalt-based alloy (stellite 6) material. The milling parameters evaluated are feed rate, cutting speed and depth of cut, a series of milling experiments are performed to measure the surface roughness data. The settings of face milling parameters were determined by using Taguchi experimental design method. Orthogonal arrays of Taguchi, the signal-to-noise (S/N) ratio, the analysis of variance (ANOVA) are employed to find the optimal levels and to analyze the effect of the milling parameters on surface roughness. Confirmation tests with the optimal levels of cutting parameters are carried out in order to illustrate the effectiveness of Taguchi optimization method. It is thus shown that the Taguchi method is very suitable to solve the surface quality problem occurring the face milling of stellite 6 material.     

微细铣削表面形貌形成分析

基于最小切削厚度的概念,提出了微细铣削过程槽底表面几何形貌仿真模型。通过微细铣削表面形貌的仿真和表面粗糙度Ra值的计算以及微细铣削实验,对微细铣削表面粗糙度随着每齿进给量变化的规律进行了分析和描述。     

Surface roughness aspects in milling MDF (medium density fibreboard)

Medium density fibreboard (MDF) is an industrial wood product. It is made out of wood waste fibres glued together with resin by heat and pressure. Nowadays MDF products are preferred over solid wood in many applications due to certain comparative advantages. Milling is the machining operation frequently used in manufacturing parts of MDF. The aim of this article is to study the influence of cutting parameters (cutting speed and feed rate) on surface roughness in MDF milling. A plan of MDF milling experiments was performed with prefixed cutting parameters. The objective was to establish correlation between cutting speed and feed rate with the surface roughness in MDF panels after milling. The surface roughness decreases with an increase of spindle speed and increases with the feed rate. The milling tests showed the important role spindle speed plays on the evolution of the surface roughness as a function of material removal rate (MRR). The advantage of using a high cutting speed in MDF milling is evident.     

车用铝合金铣削参数优化及表面质量研究

LY12铝合金是一种常见的汽车轻量化材料,为了实现铝合金材料的高效高质量制造,以铣削过程中铣削用量的选取范围为约束条件,建立以材料去除率最高和表面粗糙度最低为目标的多目标优化模型。通过铣削加工正交试验,采用回归分析方法,建立表面粗糙度预测模型;利用多目标线性规划法求出多目标优化模型的最优解。最后通过分析铣削用量对表面质量的影响得出:在给定的铣削参数范围内,主轴转速和进给速度对表面粗糙度的影响最为显著,侧吃刀量次之,而背吃刀量影响最小。     

Selection of optimum tool geometry and cutting conditions using a surface roughness prediction model for end milling

Influence of tool geometry on the quality of surface produced is well known and hence any attempt to assess the performance of end milling should include the tool geometry. In the present work, experimental studies have been conducted to see the effect of tool geometry (radial rake angle and nose radius) and cutting conditions (cutting speed and feed rate) on the machining performance during end milling of medium carbon steel. The first and second order mathematical models, in terms of machining parameters, were developed for surface roughness prediction using response surface methodology (RSM) on the basis of experimental results. The model selected for optimization has been validated with the Chi square test. The significance of these parameters on surface roughness has been established with analysis of variance. An attempt has also been made to optimize the surface roughness prediction model using genetic algorithms (GA). The GA program gives minimum values of surface roughness and their respective optimal conditions.     

An experimental investigation on the machining characteristics of microscale end milling

This paper discusses an experimental approach to assess the machining characteristics in microscale end milling operation through a systematic experimentation procedure. Microchannels were machined on brass plates using a carbide end mill of 1?mm diameter to analyze the effect of chip load (feed per tooth) and cutting speed on the surface roughness, specific cutting pressure, and cutting forces during microend milling operation. The tangential and radial components of forces were analyzed with the help of a three-dimensional model using the force signals acquired through KISTLER dynamometer. Feed per tooth and the interaction of cutting speed and chip load were identified as the critical parameters affecting the surface roughness of microchannel. Applying the concept of elastic recovery on the side wall surface of microchannels, the minimum chip thickness during the above micromilling operation was evaluated as 0.97???m, and the result was validated by the drastic increase in specific cutting pressure and erratic behavior of cutting forces below a chip load of 1???m.     

Evaluation of machinability according to the changes in machine tools and cooling lubrication environments and optimization of cutting conditions using Taguchi method

This study analyze the effect of machine tools, cooling lubrication environments and cutting conditions on surface roughness and cutting force, and propose the combination of cutting conditions which minimizes the effect of machine tool variables on the dispersion of cutting force and surface roughness by treating the changes in machine tool itself and the installation environments as a noise factors. To do so, the Taguchi method is used to establish an experiment plan, and flat end milling is carried out to measure cutting force and surface roughness. The research results show that in the case of cutting force, the effect of cutting conditions is dominant, and changes in machine tools and cooling lubrication environments barely have effect on cutting force. However, in the case of surface roughness, all of the cutting conditions, machine tool and cooling lubrication environment variables have impact. In order to select a combination of cutting conditions insensible to changes in machine tools, considerations for feed per revolution and axial depth of cut turn out most important in the aspect of cutting force, and considerations for feed per revolution is most important in the surface roughness.     

An experimental investigation on the process parameters influencing machining forces during milling of carbon and glass fiber laminates

Milling is the most feasible machining operation for producing slots and keyways with a well defined and high quality surface. Milling of composite materials is a complex task owing to its heterogeneity and the associated problems such as surface delamination, fiber pullout, burning, fuzzing and surface roughness. The machining process is dependent on the material characteristics and the cutting parameters. An attempt is made in this work to investigate the influencing cutting parameters affecting milling of composite laminates. Carbon and glass fibers were used to fabricate laminates for experimentations. The milling operation was performed with different feed rates, cutting velocity and speed. Numerically controlled vertical machining canter was used to mill slots on the laminates with different cutting speed and feed combinations. A milling tool dynamo meter was used to record the three orthogonal components of the machining force. From the experimental investigations, it was noticed that the machining force increases with increase in speed. For the same feed rate the machining force of GFRP laminates was observed to be very minimal, when compared to machining force of CFRP laminates. It is proposed to perform milling operation with lower feed rate at higher speeds for optimal milling operation.     

Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations

Optimization of cutting parameters is valuable in terms of providing high precision and efficient machining. Optimization of machining parameters for milling is an important step to minimize the machining time and cutting force, increase productivity and tool life and obtain better surface finish. In this work a mathematical model has been developed based on both the material behavior and the machine dynamics to determine cutting force for milling operations. The system used for optimization is based on powerful artificial intelligence called genetic algorithms (GA). The machining time is considered as the objective function and constraints are tool life, limits of feed rate, depth of cut, cutting speed, surface roughness, cutting force and amplitude of vibrations while maintaining a constant material removal rate. The result of the work shows how a complex optimization problem is handled by a genetic algorithm and converges very quickly. Experimental end milling tests have been performed on mild steel to measure surface roughness, cutting force using milling tool dynamometer and vibration using a FFT (fast Fourier transform) analyzer for the optimized cutting parameters in a Universal milling machine using an HSS cutter. From the estimated surface roughness value of 0.71 μm, the optimal cutting parameters that have given a maximum material removal rate of 6.0×10³ mm³/min with less amplitude of vibration at the work piece support 1.66 μm maximum displacement. The good agreement between the GA cutting forces and measured cutting forces clearly demonstrates the accuracy and effectiveness of the model presented and program developed. The obtained results indicate that the optimized parameters are capable of machining the work piece more efficiently with better surface finish.     

Precision surface characterization for finish cylindrical milling with dynamic tool displacements model

In this work a new approach to surface roughness parameters estimation during finish cylindrical end milling is presented. The proposed model includes the influence of cutting parameters, the tool’s static run out and dynamic phenomena related to instantaneous tool deflections. The modeling procedure consists of two parts. In the first stage, tool working part instantaneous displacements are estimated using an analytical model which considers tool dynamic deflections and static errors of the machine – tool-holder – tool system. The obtained height of the tool’s displacement envelope is then applied in the second stage to the calculation of surface roughness parameters. These calculations assume that in the cylindrical milling process, two different mechanisms of surface profile formation exist. Which mechanism is present is dependent on the feed per tooth and the maximum height of the tool’s displacement envelope. The developed model is validated during cylindrical milling of hardened hot-work tool steel 55NiCrMoV6 using a stylus profiler and scanning laser vibrometer over a range of cutting parameters. The surface roughness values predicted by the developed model are in good agreement with measured values. It is found that the employment of a model which includes only the effect of static displacements gives an inferior estimation of surface roughness compared to the model incorporating dynamic tool deflections.     

The development of an in-process surface roughness adaptive control system in end milling operations

An in-process surface roughness adaptive control (ISRAC) system in end milling operations was researched and developed. A multiple regression algorithm was employed to establish two subsystems: the in-process surface roughness evaluation (ISRE) subsystem and the in-process adaptive parameter control (IAPC) subsystem. These systems included not only machine cutting parameters such as feed rate, spindle speed, and depth of cut, but also cutting force signals detected by a dynamometer sensor. The multiple-regression-based ISRE subsystem predicted surface roughness during the finish cutting process with an accuracy of 91.5%. The integration of the two subsystems led to the ISRAC system. The testing resulted in a 100% success rate for adaptive control, proving that this proposed system could be implemented to adaptively control surface roughness during milling operations. This research suggests that multiple linear regression used in this study was straightforward and effective for in-process adaptive control.