Adaptive control of the WEDM process using a self-tuning fuzzy logic algorithm with grey prediction

A control system to improve the efficiency of machining a workpiece with varying thickness in the wire electrical discharge machining (WEDM) process is proposed. The abnormal ratio R _ab defined by the proportion of abnormal sparks in a sampling period is taken as the controlled variable. It is allowed to reduce temporarily as the cutting thickness is changing. A gain self-tuning fuzzy control algorithm is used so that the transient situation as the cutting thickness is suddenly increasing can be suppressed immediately, and a stable performance can be achieved. In addition, the grey predictor is adopted to compensate the time-delayed R _ab caused by the low-pass filter data processing. Experiments reveal that there is a slight variance in the optimal reference of R _ab when the cutting thickness is larger than 20 mm, and its value is set to 55% in these cases. Three cases were tested: the constant machining parameters, the constant R _ab and the proposed adaptive R _ab . The results show that the cutting speed can be obviously improved by the proposed control strategy.     

On-line Estimation of Workpiece Height by Using Neural Networks and Hierarchical Adaptive Control of WEDM

Wire breakage and unstable machining drastically reduce the machining efficiency and accuracy in wire electrical discharge machining (WEDM). When a stair-shaped workpiece is machined, poor electrolyte flow around the steps leads to wire rupture or unstable machining. This paper presents a WEDM adaptive control system that maintains optimal machining and improves the stability of machining at the stair section where workpiece thickness changes. A three-layer back propagation neural network is used to estimate the thickness of a workpiece. The developed adaptive control system is executed in the hierarchical structure of three control loops, using fuzzy control strategy. In the first control loop, the total sparking frequency is controlled within a safe level for wire rupture suppression. In the second control loop, the proportion of abnormal sparks is maintained at a pre-determined level for process control purposes. Based on the estimated thickness of a workpiece, adaptive parameter optimisation is carried out to determine the optimal machining settings and to provide the reference targets for the other two control loops. Experimental results demonstrate that the workpiece height can be estimated by using a feed-forward neural network. The developed adaptive control system results in faster machining and better machining stability than does the commonly used gap voltage control system.     

The Effect of Cutting Parameters on Workpiece Surface Roughness in Wire EDM

In this study, the variation of workpiece surface roughness with varying pulse duration, open circuit voltage, wire speed and dielectric fluid pressure was experimentally investigated in Wire Electrical Discharge Machining (WEDM). Brass wire with 0.25 mm diameter and SAE 4140 steel with 10 mm thickness were used as tool and workpiece materials in the experiments, respectively. It is found experimentally that the increasing pulse duration, open circuit voltage and wire speed, increase the surface roughness whereas the increasing dielectric fluid pressure decreases the surface roughness. The variation of workpiece surface roughness with machining parameters is modelled by using a power function. The level of importance of the machining parameters on the workpiece surface roughness is determined by using analysis of variance (ANOVA).     

A self-learning fuzzy controller for wire rupture prevention in WEDM

Wire breaking is a serious problem in the application of wire electrical discharge machining (WEDM). A WEDM sparking frequency monitoring and control system based on the characteristics of the voltage waveform of WEDM is developed. Two types of wire breaking phenomena are categorised according to the duration of the symptoms: a sudden rise of sparking frequency, and a sluggish rise of sparking frequency. Based on these results, a new self-learning fuzzy controller (SLFC) is proposed. The pulse off-time is regulated in real-time to keep the sparking frequency at a safe level so that wire breaking can be prevented. Experimental results show that this monitoring and control system can control the sparking frequency at an optimal high metal removal rate level without the risk of wire rupture.     

Study of machining parameters optimization for different materials in WEDM

In process planning of wire electrical discharge machining (WEDM), determination of appropriate machining conditions is likely to face problems in many ways. In addition to the construction of the relationship between machining parameters and machining characteristics, optimization search technique, a large number of experiments must be conducted repeatedly to renew parameters for different workpiece materials. The concept of specific discharge energy (SDE) was employed in this paper to represent the WEDM property of workpiece materials as one of the machining parameters. Two kinds of materials with distinctive SDE values, i.e., higher and lower, respectively, were selected for our experiments. The experimental data obtained were used, and a neural network that can accurately predict the relationship between machining parameters and machining characteristics was constructed. It was found that the predicted error was less than 7 %. The optimization technique of genetic algorithms was employed, and the optimal combination of machining parameters that meet the required machining characteristics for different workpiece materials was obtained. The system proposed in this study is both user-friendly and practical. It can save considerable time and cost during the construction of the database for the expert system of process planning.     

慢走丝电火花线切割粗加工仿真系统的开发

为对电火花线切割加工机理有更深刻的认识,了解加工参数对加工精度的影响规律,介绍了一个电火花线切割加工粗加工的仿真系统。仿真系统通过对放电点的探索、工件的去除以及对线电极丝振动的分析,将实际的加工现象形象地再现于计算机上。为证实仿真系统的正确性,将仿真结果与试验结果进行了比较。在试验结果的获取中,为能够得到很难测量的线电极周围的放电间隙和工件形状数据,提出一种新的三维形状测量方法。通过对仿真结果和试验结果的比较,定性地证明了仿真方法的正确性。研究结果表明:改变线电极张力及伺服电压值时,从仿真过程得到的加工形状结果与试验得到的加工形状结果其倾向基本一致;加工缝端部的形状呈凸形还是呈凹形,取决于加工过程中放电爆发力和静电引力的相对大小。     

Using wire electrical discharge machining for improved corner cutting accuracy of thin parts

The wire electrical discharge machining process (WEDM) allows one to achieved ruled surfaces along intricate contours in hard materials. When one intends to use such a machining process, one has to analyze both the magnitudes of the corners’ radii and the corner’s angles that are formed between adjoining surfaces. Some experimental research work carried out unveiled the systematic occurrence of machining errors when WEDM is used to obtain outside sharp corners, especially in small thickness workpieces. A permanent bending at the crest of sharp corners, which leads to a substantial deviation from the prescribed geometrical shape, was found. The deviation form depends on the magnetic properties of the workpiece material. The research was focused on establishing a means for characterizing this shape error. Moreover, the influence exerted by certain factors, such as the corner angle and the thickness of the workpiece on the above-mentioned machining error was quantified.     

Effect of electrode material in wire electro discharge machining characteristics of Ti50Ni50−xCux shape memory alloy

TiNiCu alloy belongs to new class of shape memory alloy (SMA), which exhibits superior properties like shape memory effect, super elasticity and reversible martensitic transformation phase and thus find broad applications in actuators, micro tools and stents in biomedical components. Even though, SMA demonstrates outstanding property profile, traditional machining of SMAs is fairly complex and hence non-traditional machining like wire electric discharge machining (WEDM) has been performed. Hence, there is a need to investigate the WEDM performance characteristics of shape memory alloys due to excellent property profile and potential applications. In the present investigation, various machining characteristics like material removal rate (MRR), surface roughness, surface topography and metallographic changes have been studied and the influence of wire material on TiNiCu alloy machining characteristics has also been evaluated through ANOVA. Ti₅₀Ni_50−xCu_{x=10, 20} was prepared by vacuum arc melting process. The proposed alloy as-cast material exhibits austenite property (B2 phase) and having higher hardness when compared to TiNi alloy. The investigation on WEDM of Ti₅₀Ni_50−xCu_x alloy reveals that the machining parameters such as servo voltage, pulse on time and pulse off time are the most significant parameters affecting MRR as well as surface roughness using both brass and zinc coated brass wires. However, machining with zinc coated brass wire yields reduced surface roughness and better MRR and also produces less surface defects on the machined surface of Ti₅₀Ni_50−xCu_x alloys.     

Comparative study of conventional and micro WEDM based on machining of meso/micro Sized Spur Gear

This paper discusses the comparison of micro machining process using conventional and micro wire electrical discharge machining (WEDM) for fabrication of miniaturized components. Seventeen toothed miniaturized spur gear of 3.5 and 1.2 mm outside diameter were fabricated by conventional and micro WEDM respectively. The process parameters for both conventional and micro WEDM were optimized by preliminary experiments and analysis. The gears were investigated for the quality of surface finish and dimensional accuracy which were used as the criteria for the process evaluation. An average surface roughness (R_a) of 50 nm and dimensional accuracy of 0.1–1 μm were achieved in micro WEDM. Whenever applied conventional WEDM for meso/micro fabrication, a R_a surface roughness of 1.8 μm and dimensional accuracy of 2–3 μm were achieved. However, this level of surface roughness and dimensional accuracy are acceptable in many applications of micro engineering. A window of conventional WEDM consisting of low energy discharge parameters is identified for micromachining.     

快走丝电火花线切割对铝材加工技术的改进

对线切割机床的加工原理进行了研究,分析了切割铝材时存在的问题,针对这些问题从机床结构改造、辅助配置和参数设置方面提出了铝材切割的改进办法,并进行了不同的试验加以验证,最终获得了满意的切割效果.     

Fabricating micromilling tool using wire electrodischarge grinding and focused ion beam sputtering

In the present research, wire electrical discharge machining (WEDM) of γ titanium aluminide is studied. Selection of optimum machining parameter combinations for obtaining higher cutting efficiency and accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complicated stochastic process mechanisms. In general, no perfect combination exists that can simultaneously result in both the best cutting speed and the best surface finish quality. This paper presents an attempt to develop an appropriate machining strategy for a maximum process criteria yield. A feed-forward back-propagation neural network is developed to model the machining process. The three most important parameters – cutting speed, surface roughness and wire offset – have been considered as measures of the process performance. The model is capable of predicting the response parameters as a function of six different control parameters, i.e. pulse on time, pulse off time, peak current, wire tension, dielectric flow rate and servo reference voltage. Experimental results demonstrate that the machining model is suitable and the optimisation strategy satisfies practical requirements.     

A novel method of determination of wire lag for enhanced profile accuracy in WEDM

Wire bending due to gap force is a major cause of imprecision in WEDM applications. To achieve higher precision and accuracy the knowledge of gap force and wire lag is extremely essential. In the present research, an in depth study on wire lag phenomenon has been carried out. A novel method to measure gap force intensity and wire lag under any given machining condition has been proposed by developing an analytical model. Experiments were carried out to verify the proposed model. Beside this, the impact of wire deflection on profile accuracy during cutting cylindrical job has been investigated. Based upon the developed analytical model an effective method has been proposed to eliminate this inaccuracy using wire lag compensation technique. The research finding will lead to better understanding of the gap force phenomena and will promote significant development in the domain of high precision WEDM.     

Surface integrity study of WEDM with various wire electrodes: experiments and analysis

Abstract

Wire electrical discharge machining (WEDM) is always significant for its high-precision machining. However, due to the generation of high discharge energy during machining, machined surfaces are often got distorted. These might be upgraded by choosing the correct tool with proper machining condition. The effects of the electrode materials and process parameters on different responses of WEDM like average surface roughness, recast layer thickness, and surface morphology are systematically examined here to enhance the knowledge of WEDM and its correlation with electrode property. The experiments have been carried out on one of the expensive steel namely Maraging steel 300 due to its applicability in tooling and aerospace industries. Plain brass wire, zinc-coated brass wire (ZCB), and silver-coated brass (SCB) wires are used as a tool electrode for analysis. Comparative experimental studies prove that among BW, ZCB, and SCB, the overall performance of SCB is commendable owing to the high-quality surface considering control parameters in low discharge energy level. However, the second-best performance is shown by ZCB.     

Strength modeling and optimizing ultrasonic welded parts of ABS-PMMA using artificial intelligence methods

This study analyzes variations in metal removal rate (MRR) and quality performance of roughness average (R _a) and corner deviation (CD) depending on parameters of wire electrical discharge machining (WEDM) process in relation to the cutting of pure tungsten profiles. A hybrid method including response surface methodology (RSM) and back-propagation neural network (BPNN) integrated simulated annealing algorithm (SAA) were proposed to determine an optimal parameter setting. The results of 18 experimental runs via a Taguchi orthogonal table were utilized to train the BPNN to predict the MRR, R _a, and CD properties. Simultaneously, RSM and SAA approaches were individually applied to search for an optimal setting. In addition, analysis of variance was implemented to identify significant factors for the processing parameters. Furthermore, the field-emission scanning electron microscope images show that a lot of built-edge layers were presented on the finishing surface after the WEDM process. Finally, the optimized result of BPNN with integrated SAA was compared with that obtained by an RSM approach. Comparisons of the results of the algorithms and confirmation experiments show that both RSM and BPNN/SAA methods are effective tools for the optimization of parameters in WEDM process.     

Theoretical and experimental analysis of machining errors on small arced corners during WEDM finishing stages

Abstract

Accurate machining in small-radius paths is a challenge associated with Wire Electrical Discharge Machining (WEDM). This article experimentally and theoretically analyzes the machining errors of the arced paths through successive machining stages. The machining errors of a three-stage WEDM on both straight and arced paths are first experimentally analyzed. Mathematical expressions are derived to relate new theoretical concepts, including spark angle and spark density, for each finishing stage on both straight and arced paths. Then, the effects of these concepts on machining errors of the finishing stages are determined. The causes of the machining errors of the first and second finishing stages on male and female arced paths are theoretically analyzed, and a novel mathematical methodology for the prediction of these errors is developed. The experimental machining errors of the first and second finishing stages on the different arced paths are compared and evaluated with related theoretical ones. Results reveal that the mathematical methodology predicts and compensates the machining errors of the first finishing stage with the accuracy of 78% and of the second finishing stage with the accuracy of 83%. There is a good improvement which can be employed in WEDM applications and to increase the wire electrical discharge (WED) machine capability.     

Performance and surface alloying characteristics of Cu–Cr and Cu–Mo powder metal tool electrodes in electrical discharge machining

The main objective of this study is to investigate the effect of Cu–Cr and Cu–Mo powder metal (PM) tool electrodes on electrical discharge machining (EDM) performance outputs. The EDM performance measures used in the study are material removal rate (MRR), tool electrode wear rate (EWR), average workpiece surface roughness (R_a), machined workpiece surface hardness, abrasive wear resistance, corrosion resistance, and workpiece alloyed layer depth and composition. The EDM performance of Cu–Cr and Cu–Mo PM electrodes produced at three different mixing ratios (15, 25, and 35 wt% Cr or Mo), compacting pressures (P_c = 600, 700, and 800 MPa), and sintering temperatures (T_s = 800, 850, and 900 °C) are compared with those machined with electrolytic Cu and Cu PM electrodes when machining SAE 1040 steel workpiece. Analyses revealed that tool materials were deposited as a layer over the work surface yielding high surface hardness, strong abrasion, and corrosion resistance. Moreover, the mixing ratio, P_c, and T_s affect the MRR, EWR, and R_a values.     

The Effect of Cutting Parameters on Wire Crater Sizes in Wire EDM

In this study, the effect of the cutting parameters on size of erosion craters (diameter and depth) on wire electrode were experimentally and theoretically investigated in wire electrical discharge machining (WEDM). The experiments were conducted under the different cutting parameters of pulse duration (300, 500, 700, and 900 ns), open circuit voltage (80, 100, and 270 V), wire speed (5, 8, and 12.5 m min ^-1 ) and dielectric flushing pressure (6, 12, and 18 kg cm ^-2 ). Brass wire of 0.25 mm diameter and AISI 4140 steel of 0.28 mm thickness were used as tool and workpiece materials in the experiments. It is found that increasing the pulse duration, open circuit voltage, and wire speed increases the crater size, whereas increasing the dielectric flushing pressure decreases the crater size. The variation of wire crater size with machining parameters is modelled mathematically by using a power function. The level of importance of the machining parameters on the wire crater size is determined by using analysis of variance (ANOVA).     

Prediction of surface roughness during abrasive flow machining

An analytical model is proposed to simulate and predict the surface roughness for different machining conditions in abrasive flow machining (AFM). The kinematic analysis is used to model the interaction between grain and workpiece. Fundamental AFM parameters, such as the grain size, grain concentration, active grain density, grain spacing, forces on the grain, initial topography, and initial surface finish (R _a value) of the workpiece are used to describe the grain-workpiece interaction. The AFM process is studied under a systematic variation of grain size, grain concentration and extrusion pressure with initial surface finish of the workpiece. Simulation results show that the proposed model gives results that are consistent with experimental results.     

Determining cutting parameters in wire EDM based on workpiece surface temperature distribution

The material removal process in wire electrical discharge machining (WEDM) may result in work-piece surface damage due to the material thermal properties and the cutting parameters such as varying on-time pulses, open circuit voltage, machine cutting speed, and dielectric fluid pressure. A finite element method (FEM) program was developed to model temperature distribution in the workpiece under the conditions of different cutting parameters. The thermal parameters of low carbon steel (AISI4340) were selected to conduct this simulation. The thickness of the temperature affected layers for different cutting parameters was computed based on a critical temperature value. Through minimizing the thickness of the temperature affected layers and satisfying a certain cutting speed, a set of the cutting process parameters were determined for workpiece manufacture. On the other hand, the experimental investigation of the effects of cutting parameters on the thickness of the AISI4340 workpiece surface layers in WEDM was used to validate the simulation results. This study is helpful for developing advanced control strategies to enhance the complex contouring capabilities and machining rate while avoiding harmful surface damage.     

PARAMETRIC INFLUENCE AND OPTIMIZATION OF WIRE EDM OF HOT DIE STEEL

Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which the electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi's technique and a Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are defined as Dimensional Error (DE), Surface Roughness (SR) and Volumetric Material Removal Rate (VMRR). Experiments were designed as per Taguchi's L₁₆ Orthogonal Array (OA) wherein Pulse-on duration, Current, Pulse-off duration, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Hot Die Steel (HDS) having the thickness of 40 mm. The Heat Affected Zone (HAZ) characteristics of the eroded materials were assessed by Scanning Electron Microscope (SEM) and the microhardness of the material was tested using Vickers microhardness tester. The results of the study reveal that among the machining parameters, it is preferable to go for smaller pulse-off duration for achieving overall good performance. Regarding pulse-on duration, higher values are recommended for error constrained machining with higher MRR and constrained/limited values for attaining good surface texture. Smaller current is suggested for better surface finish/texture control, medium range for error control and high value for MRR. Finally, the validation exercise was performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.