Vinod Yadava

Intelligent Modeling and Multiobjective Optimization of Die Sinking Electrochemical Spark Machining Process

Die sinking–electrochemical spark machining (DS–ECSM) is one of the hybrid machining processes, combining the features of electrochemical machining (ECM) and electro-discharge machining (EDM), used for machining of nonconducting materials. This article reports an intelligent approach for the modelling of DS–ECSM process using finite element method (FEM) and artificial neural network (ANN) in integrated manner. It primarily comprises development of two models. The first one is the development of a thermal finite element model to estimate the temperature distribution within the heat-affected zone (HAZ) of single spark on the workpiece during DS–ECSM. The estimated temperature field is further post-processed for determination of material removal rate (MRR) and average surface roughness (ASR). The second one is a back propagation neural network (BPNN)-based process model used in a simulation study to find optimal machining parameters. The BPNN model has been trained and tested using the data generated from the FEM simulations. The trained neural network system has been used in predicting MRR and ASR for different input conditions. The ANN model is found to accurately predict DS–ECSM process responses for chosen process conditions. This article also presents an effective approach for multiobjective optimization of DS–ECSM process using grey relational analysis.

Optimization of Cut Quality Characteristics during Nd:YAG Laser Straight Cutting of Ni-Based Superalloy Thin Sheet Using Grey Relational Analysis with Entropy Measurement

This article presents application of a hybrid approach for the optimization of Nd:YAG laser straight cutting of Ni-based superalloy thin sheet with multiple performance characteristics. The approach first finds the experimental results using Taguchi-based experimental design. The designed experimental results are used in the grey relational analysis (GRA) for optimization of multiperformance characteristics simultaneously. The quality characteristics considered are average kerf taper (T a ) and average surface roughness (R a ) measured through Optical Measuring Microscope and Surface Roughness Tester, respectively. The essential process input parameters were identified as oxygen pressure, pulse width, pulse frequency, and cutting speed. The entropy measurement method is specially employed to evaluate the values of weights corresponding to each performance characteristics so that their relative significance can be properly described. The results of confirmation experiments verify that the proposed grey-based Taguchi method has the ability to find out the optimal laser cutting parameters with multiple quality characteristics. The application of grey relational analysis has reduced T a and R a by 56% and 18%, respectively.

Multiresponse Optimization of Electro-Discharge Diamond Face Grinding Process Using Robust Design of Experiments

This article presents an investigation of the machining parameters design for electro-discharge diamond face grinding (EDDFG). The setup for EDDFG was developed, and experiments were conducted on tungsten carbide cobalt (WC-10wt%Co) composite workpiece. The input machining parameters used in the present study were wheel speed, current, pulse on time, and duty factor. The settings of machining parameters were determined by using Taguchis robust design approach. The machining parameters were optimized with multiresponse characteristics of material removal rate (MRR), wheel wear rate (WWR), and average surface roughness (ASR). Multiresponse signal-to-noise (MSNR) ratio was applied to measure the performance characteristics deviating from the actual value. Analysis of variance (ANOVA) was employed to identify the level of importance of the machining parameters on the multiple performance characteristics considered. Finally, experimental confirmation was carried out to identify the effectiveness of this proposed method.

Experimental Study of Traveling Wire Electrochemical Spark Machining of Borosilicate Glass

Machining performance study of newly developed machining processes has always been a challenge to make them industrially viable. Traveling wire electrochemical spark machining (TW-ECSM) is a newly developed hybrid process in the area of nontraditional machining process which can be effectively utilized for difficult-to-cut electrically nonconductive very hard and brittle materials. Present paper discusses the investigations showing the effect of input process variables on material removal rate (MRR) and kerf width (K w) during the cutting of borosilicate glass using self-developed tabletop TW-ECSM setup. The experimental studies are conducted under varying applied voltage, pulse-on time, pulse-off time, electrolyte concentration, and wire feed velocity. The experimental results shows that MRR and K w increase with increase in applied voltage as well as pulse-on time, but these performance characteristics decrease with increase in pulse-off time. MRR and K w increase with increase in electrolyte concentration at certain value (25% wt.) and beyond that value they start to decrease. Moreover the machined kerf width and surface finish were also analyzed by scanning electron microscope (SEM).

Multiobjective optimization of slotted electrical discharge abrasive grinding of metal matrix composite using artificial neural network and nondominated sorting genetic algorithm

The alternative use of electrical discharge grinding and abrasive grinding, which is applied with the application of slotted wheel named as slotted electrodischarge abrasive grinding, is much suitable for machining of metal matrix composites. But the selection of process parameters is a difficult task due to the complexity of the process. The aim of this study is to optimize the process parameters of slotted electrodischarge abrasive grinding process using a combined approach of artificial neural network and nondominated sorting genetic algorithm II. The artificial neural network architecture has been trained and tested with experimental data, and then the developed model is coupled with nondominated sorting genetic algorithm II to develop a hybrid approach of artificial neural network–nondominated sorting genetic algorithm II, which is used for optimization of process parameters. During experimentation, the effect of current, pulse on-time, pulse off-time, wheel speed and grit number has been studied on material removal rate and average surface roughness (Ra). The results have shown that prediction capability of artificial neural network model is within the range of acceptable limits. The developed hybrid approach of artificial neural network–nondominated sorting genetic algorithm II gives optimal solution with correlation coefficient of material removal rate and Ra as 0.9979 and 0.9982, respectively.

Development and Experimental Study of Electrodischarge Face Grinding

Electrodischarge face grinding (EDFG) process has been developed for machining of flat surfaces of materials that are difficult to machine by creating spark between face of disc shape rotating tool electrode and workpiece.The rotation of non-abrasive disc shape tool electrode about vertical axis (a new feature of face grinding) improves material removal rate (MRR) and average surface roughness (ASR) because of effective flushing of working gap. This paper presents the effect of input process parameters of EDFG, such as discharge current, pulse on-time and off-time, and wheel speed on MRR and ASR during machining of high carbon steel and high speed steel workpieces. An attempt has also been made to compare the results with those of stationary electrodes.

Experimental Investigations to Study Electrical Discharge Diamond Cutoff Grinding (EDDCG) Machinability of Cemented Carbide

The present investigation aims at evaluating the performance of electrical discharge diamond cutoff grinding (EDDCG) of cemented carbide. EDDCG is an abrasive based hybrid process consisting of diamond cutoff grinding (DCG) and electrical discharge cutoff grinding (EDCG) and is a playing major role in the processing of modern materials viz. cemented nitrides, titanium alloys, super alloys, composites of metal matrix, cemented carbides, etc. This article investigates the influence of four different parameters viz. rates per minute (RPM) of wheel, gap current, on-time (t on ), and duty factor (d f ) on material removal rate (MRR) and surface roughness (Ra). Large numbers of experiments were performed on indigenously built EDDCG set up mounted as an attachment on electrical discharge machining (EDM). The experimental results reveal that Ra increases with an increase of gap current and as well as d f but decreases with an increase of wheel RPM. Further, it also shows that the MRR rises with rise in wheel RPM, gap current, and t on but decreases as d f increases. After machining of cemented carbide workpiece by EDDCG process, the scanning electron microscope (SEM) micrographs of the machined surface were observed to study the combined effect of mechanical and electroerosion process.

Experimental Investigation of Vibration Assisted Cylindrical–Magnetic Abrasive Finishing of Aluminum Workpiece

Machining by abrasion is the most labor intensive and critical machining process to provide high quality finish on the parts. Abrasive finishing operations are usually applied as the last machining operation and its importance becomes more vital when the workpiece material is difficult-to-machine. Recently the promising processes of abrasion for difficult-to-machine materials have been developed. Magnetic abrasive finishing (MAF) is such process which utilizes the magnetic energy for finishing. During MAF, the workpiece is set between the two magnetic poles, and the working area between the workpiece and each pole is filled with the mixture of ferromagnetic particle and abrasives. The process has the wide variety of industrial application due to low specific energy consumptions. This work reports about the development of new vibration assisted cylindrical–magnetic abrasive finishing (VAC–MAF) setup and the experimental investigation of various process parameters viz. frequency of vibration, rotational speed, size of the abrasive particles, and magnetic flux density on VAC–MAF setup during finishing of aluminium workpieces.

Experimental Investigation on Electrical Discharge Drilling of Ti-6Al-4V Alloy

This article describes the experimental investigation related to creation of holes in aerospace titanium alloy workpiece using static electrode machining and electrical discharge drilling (EDD) process. Special attachment for holding and rotating the tool electrode was developed and installed on electrical discharge machining (EDM) machine by replacing the original conventional tool holder provided on die sinking EDM. The effect of input parameters such as gap current, pulse on-time, duty factor and RPM of tool electrode on output parameters for average hole circularity (Ca) and average surface roughness (Ra) have been studied. It is observed that the effect of rotating electrode machining has considerable influence on the output parameters over stationary electrode machining. The micro-graphs and photographs of few selected samples were taken by SEM and metallurgical microscope, which also commensurate with the findings of the study.

Cylindrical Electrochemical Magnetic Abrasive Machining of AISI-304 Stainless Steel

This work presents the machining performance of cylindrical electrochemical magnetic abrasive machining for high efficiency machining of cylindrical surfaces. Experiments were conducted on self-developed process setup for machining of AISI-304 stainless steel workpiece based on central composite rotatable design technique of response surface methodology. The effect of different process variables (viz. workpiece rotational speed, current to electromagnet, electrolytic current and frequency of vibration) on output responses (viz. material removal [MR], surface roughness [Ra]) is investigated. Analysis of the model shows that the workpiece rotational speed and electrolytic current have a significant influence on MR and Ra. Increasing both the workpiece rotational speed and electrolytic current leads to significant increase in MR and simultaneous reduction in Ra due to synergistic effect of abrasion-assisted passivation and passivation-assisted abrasion.