Sehijpal Singh

Effect of Silicon Powder Mixed EDM on Machining Rate of AISI D2 Die Steel

In this paper, the effect of silicon powder mixing into the dielectric fluid of EDM on machining characteristics of AISI D2 (a variant of high carbon high chrome) die steel has been studied. Six process parameters, namely peak current, pulse-on time, pulse-off time, concentration of powder, gain, and nozzle flushing have been considered. The process performance is measured in terms of machining rate (MR). The research outcome will identify the important parameters and their effect on MR of AISI D2 in the presence of suspended silicon powder in a kerosene dielectric of EDM. The study indicated that all the selected parameters except nozzle flushing have a significant effect on the mean and variation in MR (S/N ratio). Optimization to maximize MR has also been undertaken using the Taguchi method. The ANOVA analysis indicates that the percentage contribution of peak current and powder concentration toward MR is maximum among all the parameters. The confirmation runs showed that the setting of peak current at a high level (16 A), pulse-on time at a medium level (100 μs), pulse-off time at a low level (15 μs), powder concentration at a high level (4 g/l), and gain at a low level (0.83 mm/s) produced optimum MR from AISI D2 surfaces when machined by silicon powder mixed EDM.

Numerical simulation of powder mixed electric discharge machining (PMEDM) using finite element method

In the present paper, an axisymmetric two-dimensional model for powder mixed electric discharge machining (PMEDM) has been developed using the finite element method (FEM). The model utilizes the several important aspects such as temperature-sensitive material properties, shape and size of heat source (Gaussian heat distribution), percentage distribution of heat among tool, workpiece and dielectric fluid, pulse on/off time, material ejection efficiency and phase change (enthalpy) etc. to predict the thermal behaviour and material removal mechanism in PMEDM process. The developed model first calculates the temperature distribution in the workpiece material using ANSYS (version 5.4) software and then material removal rate (MRR) is estimated from the temperature profiles. The effect of various process parameters on temperature distributions along the radius and depth of the workpiece has been reported. Finally, the model has been validated by comparing the theoretical MRR with the experimental one obtained from a newly designed experimental setup developed in the laboratory.

Experimental Studies on Mechanism of Material Removal in Abrasive Flow Machining Process

In this article, the mechanism of material removal (MR) in Abrasive Flow Machining (AFM) process has been studied. Representative components of pure Aluminum and Brass were processed by AFM under similar process conditions. The processed surfaces were analyzed with the help of Scanning Electron Microscopy (SEM). SEM photographs reveal noticeable difference between abrasion patterns produced on the processed surfaces of both the materials. A mechanism of MR has been proposed by examining the nature of interaction between the flowing abrasive medium and target work surfaces of selected materials.

An experimental study of the machining parameters in powder mixed electric discharge machining of Al–10%SiCP metal matrix composites

The aim of this present research is to establish optimum process conditions for Powder Mixed Electric Discharge Machining (PMEDM) of Al–10%SiCP Metal Matrix Composites (MMC) by an experimental investigation using Response Surface Methodology (RSM). Aluminium powder was suspended into the dielectric fluid of Electric Discharge Machining (EDM). A modified powder mixed dielectric circulation system was developed in the laboratory for experimentation. Relationships are developed between various input process parameters (concentration of the added aluminium powder, peak current and pulse duration) and output characteristics (Machining Rate (MR), Surface Roughness (SR)). The obtained result allowed how to find the most important parameters and determine the optimal values that maximise the MR and minimise the SR. The recommended optimal process conditions have been verified by conducting confirmation experiments.

Effect of cryogenic treated brass wire electrode on material removal rate in wire electrical discharge machining

In this article, the effect of cryogenic treatment on the brass wire electrode used in wire electrical discharge machining is investigated. Deep cryogenic (−184°C) treatment is given to the brass wire electrode. The microstructure and crystalline phase of deep and non-cryogenic treated brass wire electrodes is observed by scanning electron microscope and X-Ray diffraction. The experimental results show that the structure is more refined in deep cryogenic treatment as compared to non-cryogenic treatment. The electrical conductivity of deep electrode is greatly improved. The effect of deep cryogenic treatment on the brass wire electrode is also investigated for the performance of wire electrical discharge machining. Taguchi experimental design has been applied to investigate the optimal parameters for maximum material removal rate. The ANOVA analysis indicates that type of wire, pulse width, time between two pulses and wire tension are significant factors for maximization of material removal rate. The cryogenic treatment results in improved material removal rate.

Optimizing Single Point Diamond Turning for Mono-Crystalline Germanium Using Grey Relational Analysis

In this paper the results of an experimental study conducted for precision machining of mono-crystalline germanium with single point diamond turning (SPDT) have been reported. The input parameters include the top rake angle, tool overhang, depth of cut, tool feed rate, and rotational speed of the workpiece. The flat profile is generated on a disk of mono-crystalline germanium possessing three performance characteristics: surface roughness (Ra), profile error (Pt), and waviness error (Wa). The process parameters are optimized to obtain the best surface finish with minimum profile and waviness errors by using the Taguchi method. The grey relational analysis is employed for carrying out multiresponse optimization of performance parameters. The best value of surface finish obtained after multiresponse optimization is 10.7 nm having a profile error and a waviness error of 0.202 µm and 0.046 µm, respectively.

Effect of Natural Fillers on Mechanical Properties of GFRP Composites

Fiber reinforced plastics (FRPs) have replaced conventional engineering materials in many areas, especially in the field of automobiles and household applications. With the increasing demand, various modifications are being incorporated in the conventional FRPs for specific applications in order to reduce costs and achieve the quality standards. The present research endeavor is an attempt to study the effect of natural fillers on the mechanical characteristics of FRPs. Rice husk, wheat husk, and coconut coir have been used as natural fillers in glass fiber reinforced plastics (GFRPs). In order to study the effect of matrix on the properties of GFRPs, polyester and epoxy resins have been used. It has been found that natural fillers provide better results in polyester-based composites. Amongst the natural fillers, in general, the composites with coconut coir have better mechanical properties as compared to the other fillers in glass/epoxy composites.

High-performance wire electrodes for wire electrical-discharge machining – a review:

In a wire electrical-discharge machining process an electrically conductive workpiece is eroded ahead of a continuous moving wire by spark discharges, which are identical with those in conventional electrical-discharge machining. With wire electrical-discharge machining, convoluted shapes can be cut with a high degree of dimensional accuracy and good surface finish. The machining efficiency of wire electrical-discharge machining can be significantly improved by an adaptive adjustment of various machining parameters, such as, pulse width, pulse interval, dielectric fluid pressure, wire tension, servo reference voltage, etc. Improving the productivities of dies and achieving high-quality workpieces demand is expanding for high-performance wire electrodes. A considerable amount of research on development of wire electrodes for wire electrical-discharge machining has explored high-performance wires for high-speed and high-precision machining. This article reviews the evolution of electrical-discharge machining wires from copper to plain brass to various coated, diffusion annealed and composite wire electrodes that significantly increase the wire electrical-discharge machining productivity. It is evident from the various research developments on wire electrode that they influence the wire electrical-discharge machining performance and improve wire electrical-discharge machining performance substantially. The possible trends for future research on electrical-discharge machining wire electrodes are also highlighted in this article.

Quality optimisation of surface finishing by magnetic field assisted abrasive flow machining through Taguchi technique

Final finishing of complex job profiles on the precision components is one of the tedious and important steps in a manufacturing process. Abrasive flow machining (AFM) is a novel technique used for obtaining a fine finish particularly on inaccessible regions. In spite of several advantages over other non-conventional machining techniques, AFM suffers from the limitation of low material removal rate. According to recent studies, abrasion rate in AFM is enhanced if the work piece is processed in the presence of a magnetic field. The introduction of a magnetic field as an assistance to AFM calls for reassessment of the process performance. In this paper, the effect of magnetic field as an input parameter along with other key parameters of AFM on the surface roughness of components is studied with the help of Taguchi technique. The optimal setting of various parameters affecting quality characteristic (surface roughness) has been also carried out.

A novel intelligent software-based approach to predict forces and delamination during drilling of fiber-reinforced plastics

Drilling of fiber-reinforced plastics (FRPs) results in drilling-induced damage which leads to reduced part life and extensive part rejection. Thus far, there exists no standard handbook or knowledge-based tool that can predict drilling-induced forces and damage. Therefore, the present research initiative is an attempt to develop a software tool based on artificial intelligence which can predict drilling-induced thrust force, torque and delamination factor during drilling of FRPs. The developed intelligent software has a friendly graphic user interface (GUI). The user just interacts through the GUI and fills the input choices, and upon execution, the software predicts the drilling forces and delamination factor. In order to generate the database for the software, drilling experiments have been performed in two different types of composite materials with four different types of drill point geometries of two distinct diameters. The drilling of composite laminate has been conducted at three different levels of spindle speed and feed rate. The software results are based on three different artificial intelligence techniques namely artificial neural network (ANN), fuzzy logic (FL) and adaptive neuro-fuzzy inference system (ANFIS). The values of thrust force, torque and delamination factor for given inputs predicted by the developed tool are in close agreement with the experimental values.