利用神经网络建立电火花加工工艺模型

以峰值电流、脉冲宽度、脉冲间隔、抬刀时间和加工时间为输入参数,以加工速度和表面粗糙度为输出参数,利用人工神经网络技术建立了电火花加工工艺模型。经过与实验数据的比较,认为该模型能精确地预测出给定条件下的加工速度和表面粗糙度,真实反映了机床的加工工艺规律。     

Electrical discharge precision machining parameters optimization investigation on S-03 special stainless steel

S-03 is a novel special stainless steel, which is widely used in precision aerospace parts and electrical discharge machining technology has the merit of high-accuracy machining. This paper aims to combine gray relational analysis and orthogonal experimental to optimize electrical discharge high-accuracy machining parameters. The four process parameters of gap voltage, peak discharge current, pulse width, and pulse interval are required to optimize in the fewest experiment times. The material removal rate and surface roughness are the objective parameters. The experiment were carried out based on Taguchi L9 orthogonal array, then we carried out the gray relational analysis to optimize the multi-objective machining parameter, finally, we verified the results through a confirmation experiment. The sequence of machining parameters from primary to secondary are as follows: discharge current 7A, pulse interval 100 μs, pulse width 50 μs, and gap voltage 70 V. Using the above machining parameters, we can obtain good surface roughness Ra1.7 μm, and material removal rate 13.3 mm³/min. The machined work piece almost has no surface modification layer. The results show that combining orthogonal experiment and gray relational analysis can further optimize machining parameters, the material removal rate increased by 23.8 %, and the surface roughness almost has no change.     

Wire electrical discharge machining of ASP30 tool steel

Wire electrical discharge machining is a non-traditional cutting process for machining of hard and high strength materials. This study analyzed the effects of the main input parameters of wire electrical discharge machining of ASP30 steel (high alloyed Powder metallurgical [PM] high speed steel) as the workpiece on the material removal rate and surface roughness. The input parameters included spraying pressure and electric conductivity coefficient of the dielectric fluid, linear velocity of the wire and wire tension. The machined surface quality was evaluated using SEM pictures. Results indicated that increasing the spraying pressure of dielectric fluid leads to a higher material removal rate and surface roughness and that increasing the wire tension, linear velocity of wire, and electric conductivity of the dielectric fluid decreases the material removal rate and surface roughness.

     

Optimization of the EDM parameters on machining Ti–6Al–4V with multiple quality characteristics

In this paper, parameter optimization of the electrical discharge machining process to Ti–6Al–4V alloy considering multiple performance characteristics using the Taguchi method and grey relational analysis is reported. Performance characteristics including the electrode wear ratio, material removal rate and surface roughness are chosen to evaluate the machining effects. The process parameters selected in this study are discharge current, open voltage, pulse duration and duty factor. Experiments based on the appropriate orthogonal array are conducted first. The normalised experimental results of the performance characteristics are then introduced to calculate the coefficient and grades according to grey relational analysis. The optimised process parameters simultaneously leading to a lower electrode wear ratio, higher material removal rate and better surface roughness are then verified through a confirmation experiment. The validation experiments show an improved electrode wear ratio of 15%, material removal rate of 12% and surface roughness of 19% when the Taguchi method and grey relational analysis are used.     

Optimization of electrical discharge machining characteristics of WC/Co composites using non-dominated sorting genetic algorithm (NSGA-II)

Electrical discharge machining (EDM) is a process for shaping hard metals and forming deep and complex shaped holes by arc erosion in all types of electro conductive materials. In the present work, the effectiveness of the EDM process with tungsten carbide and cobalt composites is evaluated in terms of the material removal rate and the surface finish quality of the workpiece produced. The objective of this research is to study the influence of operating parameters of EDM such as pulse current, pulse on time, electrode rotation and flushing pressure on material removal rate and surface roughness. The experimental results are used to develop the statistical models based on second order polynomial equations for the different process characteristics. The non-dominated sorting genetic algorithm (NSGA-II) has been used to optimize the processing conditions. A non-dominated solution set has been obtained and reported.     

非电参数对非导电工程陶瓷电火花磨削效果的影响

开发了一种新的非导电工程陶瓷电火花磨削工艺,对不导电的A1203工程陶瓷进行了加工实验研究,给出了一些非电参数对材料去除率和工件表面粗糙度的影响规律,并进行了理论分析.结果表明,非电参数在该加工工艺中起到举足轻重的作用,设置合理可以大大提高材料去除率,并能改善工件表面质量.     

Empirical modeling and optimization of wire electrical discharge machining

Wire electrical discharge machining is a widely used process in manufacturing industries to machine complex profiles. The performance of any machining process is based on choosing the right combination of input parameters. Metal removal rate and surface roughness are the most important output parameters, which decide the performance of a machining process. The selection of optimal parameters in wire electrical discharge machining is difficult as it is a complex process and involves a large number of variables. The present work models the metal removal rate and the surface roughness in terms of the input variables using the response surface methodology and, consequently, the developed mathematical models are utilized for optimization. Since the influences of machining parameters on the metal removal rate and the surface roughness are opposite, the problem is formulated as a multiobjective optimization problem. Non-dominated sorting genetic algorithm is then applied to obtain the Pareto-optimal set of solutions.     

Optimization of multi machining characteristics in WEDM of WC-5.3%Co composite using integrated approach of Taguchi,GRA and entropy method

Wire electrical discharge machining (WEDM) is a well known process for generating intricate and complex geometries in hard metal alloys and metal matrix composites with high precision. In present work, intricate machining of WC-5.3%Co composite on WEDM has been reported. Taguchi’s design of experiment has been utilised to investigate the process parameters for four machining characteristics namely material removal rate, surface roughness, angular error and radial overcut. In order to optimize the four machining characteristics simultaneously, grey relational analysis (GRA) coupled with entropy measurement method has been employed. Through GRA, grey relational grade has been computed as a performance index for predicting the optimal parameters setting for multi machining characteristics. Using Analysis of Variance (ANOVA) on grey relational grade, significant parameters affecting the multi-machining characteristics has been determined. Confirmatory results prove the potential of present approach.     

Diamond face grinding of WC-Co composite with spark assistance: Experimental study and parameter optimization

Electro-discharge machining (EDM) characteristics of tungsten carbide-cobalt composite are accompanied by a number of problems such as the presence of resolidified layer, large tool wear rate and thermal cracks. Use of combination of conventional grinding and EDM (a new hybrid feature) has potential to overcome these problems. This article presents the face grinding of tungsten carbide-cobalt composite (WC-Co) with electrical spark discharge incorporated within face of wheel and flat surface of cylindrical workpiece. A face grinding setup for electro- discharge diamond grinding (EDDG) process is developed. The effect of input parameters such as wheel speed, current, pulse on-time and duty factor on output parameters such as material removal rate (MRR), wheel wear rate (WWR) and average surface roughness (ASR), are investigated. The present study shows that MRR increases with increase in current and wheel speed while it decreases with increase in pulse on-time for higher pulse on-time (above 100 μs). The most significant factor has been found as wheel speed affecting the robustness of electro- discharge diamond face grinding (EDDFG) process.     

Analysis and predictive modeling of performance parameters in electrochemical drilling process

In this paper, the effect of feed rate, voltage, and flow rate of electrolyte on some performance parameters such as surface roughness, material removal rate, and over-cut of SAE-XEV-F valve-steel during electrochemical drilling in NaCl and NaNo₃ electrolytic solutions have been studied using the main effect plot, the interaction plot and the ANOVA analysis. In continuation, in this case which the training dataset was small, an investigation has been done on the capability of the optimum presented regression analysis (RA), artificial neural network (ANN), and co-active neuro-fuzzy inference system (CANFIS) to predict the surface roughness, material removal rate and over-cut. The predicted parameters by the employed models have been compared with the experimental data. The comparison of results indicated that in electrochemical drilling using different electrolytic solutions, CANFIS gives the best results to predict the surface roughness and over-cut as well, while ANN is the best for predicting the material removal rate.     

Multi-objective optimization of material removal rate and surface roughness in wire electrical discharge turning

Wire electrical discharge turning (WEDT) is an emerging area, and it can be used to generate cylindrical forms on difficult to machine materials by adding a rotary axes to WEDM. The selection of optimum cutting parameters in WEDT is an important step to achieve high productivity while making sure that there is no wire breakage. In the present work, the WEDT process is modelled using an artificial neural network with feed-forward back-propagation algorithm and using adaptive neuro-fuzzy inference system. The experiments were designed based on Taguchi design of experiments to train the neural network and to test its performance. The process is optimized considering the two output process parameters, material removal rate, and surface roughness, which are important for increasing the productivity and quality of the products. Since the output parameters are conflicting in nature, a multi-objective optimization method based on non-dominated sorting genetic algorithm-II is used to optimize the process. A pareto-optimal front leading to the set of optimal solutions for material removal rate and surface roughness is obtained using the proposed algorithms. The results are verified with experiments, and it is found to improve the performance of WEDT process. Using this set of solutions, required input parameters can be selected to achieve higher material removal rate and good surface finish.     

Application of Taguchi-grey multi responses optimization on process parameters in electro erosion

Convention Taguchi method deals with only single response optimization problems. Since the electrical discharge machining process involved with many response parameters, Taguchi method alone cannot help to obtain optimal process parameters in such process. In the present work, an endeavor has been made to derive optimal combination of electrical process parameters in electro erosion process using grey relational analysis with Taguchi method. This multi response optimization of the electrical discharge machining process has been conducted with AISI 202 stainless steel with different tool electrodes such as copper, brass and tungsten carbide. Gap voltage, discharge current and duty factor have been used as electrical excitation parameters with different process levels. Taguchi L₂₇ orthogonal table has been assigned for conducting experiments with the consideration of interactions among the input electrical process parameters. Material removal rate, electrode wear rate and surface roughness have been selected as response parameters. From the experimental results, it has been found that the electrical conductivity of the tool electrode has the most influencing nature on the machining characteristics in EDM process. The optimal combination of the input process parameters has been obtained using Taguchi-grey relational analysis.     

Research on electrochemical discharge-assisted diamond wire cutting of insulating ceramics

Insulating ceramics are difficult to cut because of their high hardness and brittleness properties. This research proposes an electrochemical discharge-assisted diamond wire method for cutting insulating ceramics. The high temperature generated from electrochemical discharge facilitates the spalling of ceramics by the moving diamond wire. Experimental results showed that the material removal rate (MRR) of the new cutting method increased compared with the conventional diamond wire cutting process. Besides, electrochemical discharge had limited influence on the surface roughness and the wear of diamond wire. Additionally, the influence of the process parameters (DC voltage, wire speed, and counterweight mass) on the MRR and surface roughness was analyzed through experiments. The results showed that the MRR and surface roughness initially increased and then decreased with the increasing DC voltage; however, the variation was little. The higher wire speed resulted in an increased MRR and had little influence on the surface roughness. The MRR and surface roughness increased with the increasing counterweight mass.     

Parametric optimization for surface roughness, kerf and MRR in wire electrical discharge machining (WEDM) using Taguchi design of experiment

This paper reports the effect and optimization of eight control factors on material removal rate (MRR), surface roughness and kerf in wire electrical discharge machining (WEDM) process for tool steel D2. The experimentation is performed under different cutting conditions of wire feed velocity, dielectric pressure, pulse on-time, pulse off-time, open voltage, wire tension and servo voltage by varying the material thickness. Taguchi’s L18 orthogonal array is employed for experimental design. Analysis of variance (ANOVA) and signal-tonoise (S/N) ratio are used as statistical analyses to identify the significant control factors and to achieve optimum levels respectively. Additionally, linear regression and additive models are developed for surface roughness, kerf and material removal rate (MRR). Results of the confirmatory experiments are found to be in good agreement with those predicted. It has been found that pulse on-time is the most significant factor affecting the surface roughness, kerf and material removal rate.     

Optimisation of process parameters for multi-performance characteristics in EDM of Al2O3 ceramic composite

The advantages of electrical discharge machining (EDM) in machining of complex ceramic components have promoted research in the area of EDM of ceramic composites. The recent developments in ceramic composites are focused not only on the improvements of strength and toughness, but also on possibilities for difficult-to-machine shapes using EDM. One such EDM-machinable ceramic composite material (Al₂O₃–SiC_w–TiC) has been developed recently and has been selected in the present study to investigate its EDM machinability. Experiments were conducted using discharge current, pulse-on time, duty cycle and gap voltage as typical process parameters. The grey relational analysis was adopted to obtain grey relational grade for EDM process with multiple characteristics namely material removal rate and surface roughness. Analysis of variance was used to study the significance of process variables on grey relational grade which showed discharge current and duty cycle to be most significant parameters. Other than discharge current and duty cycle, pulse-on time and gap voltage have also been found to be significant. To validate the study, confirmation experiment has been carried out at optimum set of parameters and predicted results have been found to be in good agreement with experimental findings.     

The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-II

In the medium-speed wire electrical discharge machining (MS-WEDM) process, the extremely high temperature and massive electrical discharges in a fraction of 1 s result in the poor surface quality such as high tensile residual stresses, high surface roughness, white layers, and micro cracks. In this paper, an experimental plan for central composite design (CCD) of processing the tool steel (SKD11) has been conducted according to response surface methodology (RSM). The aim is to develop the mathematical model that can correlate the main process parameters of MS-WEDM with machining performance and to seek the optimal parameters on material removal rate (MRR) and 3D surface quality (Sq) by integrated RSM and Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Then, a set of pareto-optimal solutions is obtained. Moreover, from the confirmation experiment, it has been proved that the optimal process-parameter combinations are suitable on the MRR and the 3D surface texture. Eventually, it has also demonstrated that the method of integrated RSM and NSGA-II is an effective way for multi-objective optimization.     

Influence of parameters and optimization of EDM performance measures on MDN 300 steel using Taguchi method

Maraging steel (MDN 300) exhibits high levels of strength and hardness. Optimization of performance measures is essential for effective machining. In this paper, Taguchi method, used to determine the influence of process parameters and optimization of electrical discharge machining (EDM) performance measures on MDN 300 steel, has been discussed. The process performance criteria such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) were evaluated. Discharge current, pulse on time, and pulse off time have been considered the main factors affecting EDM performance. The results of the present work reveal that the optimal level of the factors for SR and TWR are same but differs from the optimum levels of the factors for MRR and RWR. Further, discharge current, pulse on time, and pulse off time have been found to play a significant role in EDM operations. Detailed analysis of structural features of machined surface was done by using scanning electron microscope (SEM) to understand the influence of parameters. SEM of electrical discharge machining surface indicates that at higher discharge current and longer pulse on duration give rougher surface with more craters, globules of debris, pockmarks or chimneys, and microcracks than that of lower discharge current and lower pulse on duration.     

Experimental investigation and analytical modelling of the effects of process parameters on material removal rate for bonnet polishing of cobalt chrome alloy

Cobalt chrome alloys are the most extensively used material in the field of total hip and total knee implants, both of which need highly accurate form and low surface roughness for longevity in vivo. In order to achieve the desired form, it is extremely important to understand how process parameters of the final finishing process affect the material removal rate. This paper reports a modified Preston equation model combining process parameters to allow prediction of the material removal rate during bonnet polishing of a medical grade cobalt chrome alloy. The model created is based on experiments which were carried out on a bonnet polishing machine to investigate the effects of process parameters, including precess angle, head speed, tool offset and tool pressure, on material removal rate. The characteristic of material removal is termed influence function and assessed in terms of width, maximal depth and material removal rate. Experimental results show that the width of the influence function increases significantly with the increase of the precess angle and the tool offset; the depth of the influence function increases with the increase of the head speed, increases first and then decrease with the increase of the tool offset; the material removal rate increases with the increase of the precess angle non-linearly, with the increase of the head speed linearly, and increases first then decreases with the increase of the tool offset because of the bonnet distortion; the tool pressure has a slight effect on the influence function. The proposed model has been verified experimentally by using different Preston coefficients from literature. The close values of the experimental data and predicted data indicate that the model is viable when applied to the prediction of the material removal rate in bonnet polishing.     

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.     

Single and multiobjective optimization of Inconel 718 nickel-based superalloy in the wire electrical discharge machining

Inconel 718 is widely used in high-temperature environments, high-performance aircraft, and hypersonic missile weapon systems; however, it is very difficult to machine using conventional techniques. This study employed an L9 Taguchi orthogonal array for the analysis of wire electrical discharge machining parameters when used for the machining of Inconel 718. Our aim was to determine the optimal combination of parameters to minimize surface roughness while maximizing the material removal rate. The Taguchi method is widely applied in mechanical engineering with the aim of identifying the optimal combination of processing parameters as they pertain to single quality characteristics. Unfortunately, Taguchi analysis often leads to contradictory results when seeking to rectify multiple objectives. To resolve this issue, this study implemented gray relational analysis in conjunction with Taguchi method to obtain the optimal combination of parameters to deal specifically with multiple quality objectives. For the dual objectives of surface roughness and material removal rate, the optimal combination of parameters derived using gray relational analysis resulted in a mean surface roughness of 2.75 μm. In L9 orthogonal array experiments, run 1 produced the best gray relational grade with mean surface roughness of 2.80 μm, representing an improvement of 1.8%. The material removal rate achieved after the application of gray relational analysis was 0.00190 g/s, whereas the L9 experiment achieved a material removal rate of 0.00123 g/s, representing an improvement of 54.5%.