Optimization of machining parameters using magnetic-force-assisted EDM based on gray relational analysis

This work developed a novel process of magnetic-force-assisted electrical discharge machining (EDM) and conducted an experimental investigation to optimize the machining parameters associated with multiple performance characteristics using gray relational analysis. The main machining parameters such as machining polarity (P), peak current (I _P), pulse duration (τ _P), high-voltage auxiliary current (I _H), no-load voltage (V), and servo reference voltage (S _V) were selected to explore the effects of multiple performance characteristics on the material removal rate, electrode wear rate, and surface roughness. The experiments were conducted according to an orthogonal array L18 based on Taguchi method, and the significant process parameters that affected the multiple performance characteristics of magnetic-force-assisted EDM were also determined form the analysis of variance. Moreover, the optimal combination levels of machining parameters were also determined from the response graph and then verified experimentally. The multiple performance characteristics of the magnetic-force-assisted EDM were improved, and the EDM technique with high efficiency, high precision, and high-quality surface were established to meet the demand of modern industrial applications.     

基于灰色关联分析的电火花加工不锈钢小孔工艺参数优化

采用DS307A高速穿孔机,开展在6mm厚不锈钢板上加工直径为1.2 mm小孔的试验研究。运用正交试验法,研究电火花加工电参数对加工时间、电极损耗和加工间隙的影响,并对试验结果进行灰色关联分析,得出最优加工参数。结果表明,经参数优化后,减少了加工时间、降低了电极损耗,以及表面粗糙度得以明显改善,满足快速精加工的技术要求。     

基于GA-RBF神经网络的电火花成形加工电参数优化

针对电火花成形加工的电参数选择问题,先建立RBF神经网络,将加工电参数和工艺指标参数分别作为神经网络的输入和输出.然后用GA优化RBF神经网络,建立用于电火花成形加工电参数优化的GA-RBF神经网络模型.试验结果表明,该网络的精度是令人满意的.     

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.     

Optimisation of machining parameters for milling operations using a scatter search approach

This paper describes the application of a newly developed metaheuristic, the scatter search, for optimising the machining parameters of milling operations. An objective function based on maximum profit is used while considering the practical constraints, such as allowable speed and feed, maximum machine power, surface finish requirement and maximum cutting speed permitted by the rigidity of the machine tool. An example is taken from the literature for comparing the results of the proposed method with other heuristics and handbook recommendations.     

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.     

A central composite design based fuzzy logic for optimization of drilling parameters on natural fiber reinforced composite

Machining of polymeric composite is inevitable during assembly of components. In view of making holes on structural composites, drilling is essential and a study to optimize the machining parameters is very important. The present study has been made to investigate the defaces and cutting forces associated during drilling of natural fiber reinforced plastics. Plastic composite has been manufactured using chemically treated vetiveria zizanioides as the reinforcement and polyester as the matrix. The composite has been drilled several times on the basis of central composite design. Speed and feed rate of the spindle, point angle and diameter of the tool are considered as the input parameters. Deface of each hole during entry and exit, thrust force and torque have been measured as the output parameters. A fuzzy model has been created and a comparative study between the central composite design and fuzzy model is made. The design has been optimized with the objective of minimizing the output parameters and a set of confirmatory experiments have been conducted. The central composite model has been validated by comparing it with the fuzzy model and confirmatory runs. The comparison presented only a minimal error and hence the modeling by central composite design and fuzzy are consummate.     

Optimization of machining parameters in rotary EDM process by using the Taguchi method

Electrical discharge machining (EDM) is one of the advanced methods of machining. Most publications on the EDM process are directed towards non-rotational tools. But rotation of the tool provides a good flushing in the machining zone. In this study, the optimal setting of the process parameters on rotary EDM was determined. A total of three variables of peak current, pulse on time, and rotational speed of the tool with three types of electrode were considered as machining parameters. Then some experiments have been performed by using Taguchi's method to evaluate the effects of input parameters on material removal rate, electrode wear rate, surface roughness, and overcut. Moreover, the optimal setting of the parameters was determined through experiments planned, conducted, and analyzed using the Taguchi method. Results indicate that the model has an acceptable performance to optimize the rotary EDM process.     

Application of the central composite design in optimization of machining parameters in drilling hybrid metal matrix composites

In this study, the application of response surface methodology (RSM) and central composite design (CCD) for modeling, optimization, and an analysis of the influences of dominant machining parameters on thrust force, surface roughness and burr height in the drilling of hybrid metal matrix composites produced through stir casting route. Experiments are carried out using Al 356-aluminum alloy reinforced with silicon carbide of size 25 μm and Mica of size 45 μm. Drilling test is carried out using carbide drill of 6 mm diameter. The design of experiment concept has been used to optimize the experimental conditions. The experimental data are collected based on a three-factor-three-level full central composite design. The multiple regression analysis using RSM is used to establish the input–output relationships of the process. The mathematical models are developed and tested for adequacy using analysis of variance and other adequacy measures using the developed models. The main and interaction effect of the input variables on the predicted responses are investigated. The predicted values and measured values are fairly close, which indicate that the developed models can be effectively used to predict the responses in the drilling of hybrid metal matrix composites. The optimized drilling process parameters have been obtained by numerical optimization using RSM by ensuring the minimum thrust force of 84 N, surface roughness of 1.67 μm, and the burr height of 0.16 mm. After the drilling experiments, a scanning electron microscope (SEM) is used to investigate the machined surface and tool wear.     

Determination of optimal EDM machining parameters for machined pure titanium-porcelain adhesion

The objective of this experimental study is to determine electrical discharge machining (EDM) parameters that offer the best adhesion at the interface of a machined titanium–porcelain composite. First of all, with Taguchi method, machining parameters that will be effective in the bonding strength as well as their interactions on each other were determined in the test. Then, multiple level experiments were conducted to determine how the effective parameters varied over a wide area. Slopes of the curves obtained in these tests were studied, and then, final tests were conducted to obtain the best bonding strength possible. In this way, machining parameters that would offer the highest bonding strength of the titanium–porcelain matrix in a stepwise adjustable EDM machine were obtained. By taking into consideration the steps on the EDM machine where the tests were conducted, it is seen that, when a full factorial experiment is undertaken, 5 power?×?2 polarity?×?2 type of dielectric?×?2 sandblasting or non-sandblasting?×?2 kind of electrode?×?10 pulse-on time, it necessitates 800 different tests to be executed, but, with the applied method, 16?+?18?+?3 yields 37 different tests where the results that include all possible alternatives were obtained. As a result, EDM machining parameters that offer the highest adhesion and are relatively higher, 31.5 N/mm², than the acceptable minimum value of 25 N/mm² were specified.     

基于神经网络和遗传算法的绝缘陶瓷电火花加工电参数优化

针对电火花加工时选取合适工艺参数(如在表面粗糙度符合要求的前提下获得最大的加工速度)困难的问题,先以神经网络建立模型,然后结合遗传算法求解此约束优化问题,得到优化的电参数.并以绝缘陶瓷材料的电火花加工为例进行说明,结果显示,取得了很好的效果.     

The design of abrasive machining operations

A consistent approach to the design of abrasive machining operations is established. Its problems are noted, along with potential means of resolution.     

Optimization techniques for machining operations: a retrospective research based on various mathematical models

Simulated annealing, genetic algorithm, and particle swarm optimization techniques have been used for exploring optimal machining parameters for single pass turning operation, multi-pass turning operation, and surface grinding operation. The behavior of optimization techniques are studied based on various mathematical models. The objective functions of the various mathematical models are distinctly different from each other. The most affecting machining parameters are considered as cutting speed, feed, and depth of cut. Physical constraints are speed, feed, depth of cut, power limitation, surface roughness, temperature, and cutting force.     

基于低碳制造的多工步孔加工切削参数优化

为实现数控加工的孔加工低碳化,建立了孔加工过程中包含消耗电能折算的碳排放、刀具折算的碳排放和切削液折算的碳排放的碳排放函数,约束条件包括机床性能参数、钻头稳定性和加工时间,以钻孔和扩孔时的切削速度、进给量和背吃刀量为优化变量。通过在某型号机床试验测得切削功率,拟合出目标函数中的机床空载功率系数和切削加工时转矩修正系数。结合试验数据分析验证所建模型的有效性。运用遗传算法对优化模型求解,结果显示碳排放量减少大约15%。     

Optimization of end mill tool geometry parameters for Al7075-T6 machining operations based on vibration amplitude by response surface methodology

This paper aims at developing a statistical model to envisage vibration amplitude in terms of geometrical parameters such as radial rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed and axial depth of cut. Experiments were conducted through response surface methodology experimental design. The material chosen is Aluminum (Al 7075-T6) and the tool used was high speed steel end mill cutter with different tool geometry. Two channels piezoelectric accelerometers were used to measure the vibration amplitude. The second order mathematical model in terms of machining parameters was built up to predict the vibration amplitude and ANOVA was used to verify the competency of the model. Further investigation on the direct and interactive effect of the process parameter with vibration amplitude was carried out for the selection of process parameter so that the vibration amplitude was maintained at the minimum which ensures the stability of end milling process. The optimum values obtained from end milling process are Radial rake angle-12°, Nose radius-0.8 mm, Cutting speed-115 m/min, Cutting feed rate-0.04 mm/tooth, axial depth of cut-2.5 mm. The vibration amplitude exhibited negative relationship with radial rake angle and nose radius. The dominant factors on the vibration amplitude are feed rate and depth of cut. Thus it is envisaged that the predictive models in this study could produce values of the vibration amplitude close to the experimental readings with a 95% confidence interval.     

A structured approach to the automatic planning of machining operations for rotational parts based on computer integration of standard design and process data

The traditional procedure for developing a manufacturing process plan involves a number of interconnected steps beginning with the initial design and culminating in the instructions for the machine that makes the part. When performed manually, the procedure is very tedious, time consuming, and often, inconsistent. This paper presents an alternative method, called the Automated Machining-Operations Process-Planning System (AMOPPS), to automatically generate the process plan and the numerical control (NC) instructions to machine a part that has been previously designed by a computer-aided design (CAD) system. AMOPPS combines preset planning logic and data from three databases (viz., workpiece material, machine tool, and cutting tool) with appropriate data from a CAD database and information from the user about the workpiece to calculate the optimal machining parameters, print a process plan, print the corresponding NC program listing, and provide an on-screen animation of the cutting passes. Although AMOPPS is a prototype, it can be extended by adding other modules, and it does provide a structure through which a fully integrated manufacturing system can be developed.     

电火花微喷孔加工控制系统的设计与研究

针对喷油嘴微喷孔加工的要求,分析与研究可加工偏心孔的高精度六轴电火花微喷孔加工设备,设计开发了机床的控制系统,解决了此类产品常规机床无法加工的难点。加工试验表明,该控制系统加工效果好,加工精度和稳定性高,可在Φ0.12 0.22mm喷油嘴上自动加工511孔数的偏心孔。微喷孔直径小于Φ0.2mm,单孔加工精度误差达到2 m,喷孔孔壁内表面粗糙度Ra小于0.6μm,完全可以满足国Ⅲ(欧Ⅲ)以上排放标准的喷油嘴微喷孔自动多孔加工的要求。     

Evaluation of the characteristics of the microelectrical discharge machining process using response surface methodology based on the central composite design

Evaluation of the characteristics of a microelectrical discharge machining (Micro-EDM) process is challenging, because it involves complex, interrelated relationships so a proper modeling approach is necessary to clearly identify the crucial machining variables and their interrelationships in order to initiate more effective strategies to improve Micro-EDM qualities (electrode wear (EW), material removal rate (MRR) and overcut). This paper uses a response surface method (RSM) based on the central composite design (CCD) for Micro-EDM problems with four EDM variables (peak current, pulse on-time, pulse off-time and electrode rotation speed). Experimental results indicate that peak current is the EDM variable that most affects the Micro-EDM qualities for SK3 carbon tool steel while pulse off-time had a significant interaction with that. The results show that RSM based on the CCD could efficiently be applied for the modeling of Micro-EDM qualities (EW, MRR, and overcut), and it is an economical way to obtain the performance characteristics of Micro-EDM process parameters with the fewest experimental data.     

基于灵敏度分析的五面加工中心床身结构优化设计

机床床身是机床的重要部件,它起着支撑立柱、工作台等部件的作用,其性能的好坏直接影响到机床的加工精度。在对HX7910五面加工中心床身结构动态优化设计过程中,建立HX7910五面加工中心床身的有限元模型,分析了其前六阶模态。根据分析结果确定筋板为优化对象,采用灵敏度优化法首先对床身内部筋板结构参数进行动态灵敏度分析。在灵敏度分析基础上,进行结构优化设计,得到了较优的结构参数,提高了加工中心床身的动态特性,从而提高床身的性能。