Experimental Study of Process Parameters through ...

Experimental Study of Process Parameters through Dissimilar Form of Electrodes in EDM Machining 1

Dalgobind Mahto1 Director, Jaipur Institute of Engineering and Technology, Kukas, Jaipur, India Email: [email protected] 2

Narinder Singh2 Green Hills Engineering College, Solan Email: [email protected] ABSTRACT

Electrical discharge machining (EDM) is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. In recent years, EDM researchers have explored a number of ways to improve the sparking efficiency including some unique experimental concepts that depart from the EDM traditional sparking phenomenon. Despite a range of different approaches, this new research shares the same objectives of achieving more efficient metal removal coupled with a reduction in tool wear and improved surface quality. This paper reviews and based on review findings the research work carried out to improve performance measures, optimizing the process variables, monitoring and control the sparking process, simplifying the electrode design and manufacture. From the experiment, it has been witnessed that current was the most significant parameter followed by pulse on time and the least significant was the pulse off time for the Material removal rate and tool wear rate. Key words: EDM, Cutting Parameters, Machine Settings and Optimal Cutting Conditions 1.0 INTRODUCTION Electrical Discharge Machining is an electro-thermal non-traditional machining process, where material is removed by thermal energy of spark occurring by means of repeated sequences of electrical ejections between the small gap of an electrode and a work piece. EDM is commonly used for machining of electrically conductive hard metals and alloys in automotive, aerospace and die making industries. EDM process is removing undesirable material in the form of debris and produce shape of the tool surface as of a metal portion by means of a recurring electrical ejection stuck between tool i.e. cathode and the work piece i.e. anode material in the existence of dielectric liquid. In this machining process work piece is called the anode because it is connected with positive terminal and electrode is connected with negative terminal i.e. called cathode. Dielectric fluid may be kerosene, transformer oil, distilled water, etc. 1.1 Principle of EDM Electrical Discharge Machining (EDM) is a controlled metal-removal process that is used to remove metal by means of electric spark erosion. In this process an electric spark is used as the cutting tool to cut (erode) the workpiece to produce the finished part to the desired shape. The metal-removal process is performed by applying a pulsating (ON/OFF) electrical charge of high-frequency current through the electrode to the workpiece. This removes (erodes) very tiny pieces of metal from the work piece at a controlled rate. Fig.1.1 shows the electric setup of the Electric discharge machining. The tool is made cathode and work piece is anode. When the voltage across the gap becomes sufficiently high it discharges through the gap in the form of the spark in interval of from 10 of micro seconds. And positive ions and electrons are accelerated, producing a discharge channel that becomes conductive. It is just at this point when the spark jumps causing collisions between ions and electrons and creating a channel of plasma. A sudden drop of the electric resistance of the previous channel allows that current density reaches very high values producing an increase of ionization and the creation of a powerful magnetic field. The moment spark occurs sufficiently pressure developed between work and tool as a result of which a very high temperature is reached and at such high pressure and temperature that some metal is melted and eroded. Such localized extreme rise in temperature leads to material removal. Material removal occurs due to instant vaporization of the material as well as due to melting. The molten metal is not removed completely but only partially.

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Figure 1.1: Working principle of EDM [1] As the potential difference is withdrawn, the plasma channel is no longer sustained. As the plasma channel collapse, it generates pressure or shock waves, which evacuates the molten material forming a crater of removed material around the site of the spark. Plasma passage occurring exciting increase of temperature make use to remove material. Material removal takes place because of on the spot vaporization of the metallic particle as well as owed to melting process. The melted particle is not withdrawn altogether, however just partly. By means of the potential difference is drawn the plasma passage is no longer continued. As the plasma passage breakdown, it produces pressure force or shock waves, which clears the molten material by flushing method making a depression of removing material all over the place of the spark. Electrical discharge machining (EDM) is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. The non-contact machining techniques have been continuously evolving from a mere tool and die making process to a micro-scale application machining alternative attracting a significant amount of research interests. In recent years, EDM researchers have explored a number of ways to improve the sparking efficiency including some unique experimental concepts that depart from the EDM traditional sparking phenomenon. Despite a range of different approaches, this new research shares the same objectives of achieving more efficient metal removal coupled with a reduction in tool wear and improved surface quality. This paper reviews the research work carried out from the inception to the development of die-sinking EDM within the past decade. It reports on the EDM research relating to improving performance measures, optimizing the process variables, monitoring and control the sparking process, simplifying the electrode design and manufacture. A range of EDM applications are highlighted together with the development of hybrid machining processes. The paper discusses these developments and outlines the trends for future EDM research. The electrode is fabricated with the reverse or negative image of the finished work piece cavity. The work piece cavity is measurably larger than the electrode. This dimensional difference is called the overcut or kerf. This kerf dimension is critical during the fabrication of the electrode. This process becomes cost-effective method of machining extremely tough and brittle materials. It is widely used for making moulds, dies and sections of complex geometry and forming deep complex shaped holes, by arc erosion in all kinds of electro-conductive materials. The material used for experiment is a low alloy steel. The input variable parameters are current, pulse on time and duty cycle. Taguchi method is applied to create an L27 orthogonal array of input variables using the Design of Experiments (DOE). The effect of the variable parameters mentioned upon the machining characteristics such as Material Removal Rate (MRR), Tool Wear Rate (TWR) is studied and investigated. The tool material is copper. The results obtained showed that current was the most significant parameter followed by pulse on time and the least significant was the pulse off time for the Material removal rate and tool wear rate. Key words: Electrical discharge machining (EDM)

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Fig 1.2: Cause and Effect Diagram of EDM 1.2 Background of electric discharge machine (EDM) Conventional Machining Processes mostly remove material in the form of chips by applying forces on the work material with a wedge shaped cutting tool that is harder than the work material under machining condition. The major characteristics of conventional machining are: • Generally macroscopic chip formation by shear deformation • Material removal takes place due to application of cutting forces – energy domain can be classified as mechanical • Cutting tool is harder than work piece at room temperature as well as under machining conditions Non-conventional Machining processes is defined as a group of processes that remove excess material by various techniques involving mechanical, thermal, electrical or chemical energy or combinations of these energies but do not use a sharp cutting tools as it needs to be used for traditional Machining processes. The major characteristics of Non-conventional machining are: 1.

Material removal may occur with chip formation or even no chip formation may take place. For example in AJM, chips are of microscopic size and in case of Electrochemical machining material removal occurs due to electrochemical dissolution at atomic level. 2. In NTM, there may not be a physical tool present. For example in laser jet machining, machining is carried out by laser beam. However in Electrochemical Machining there is a physical tool that is very much required for machining 3. In NTM, the tool need not be harder than the work piece material. For example, in EDM, copper is used as the tool material to machine hardened steels. 4. Mostly NTM processes do not necessarily use mechanical energy to provide material removal. They use different energy domains to provide machining. For example, in USM, AJM, WJM mechanical energy is used to machine material, whereas in ECM electrochemical dissolution constitutes material removal. Industries like aeronautics, automobiles, nuclear reactors, missiles etc. requires materials like high strength temperature resistant alloys which have higher strength, corrosion resistance, toughness and other properties. So it has become essential to develop cutting materials and processes which can safely and conveniently machine such new materials with good productivity, high accuracy. This can be achieved by non-conventional methods. These processes do not use cutting tool instead use energy in direct form to remove materials from work pieces. Applications of these processes are determined by work piece properties like electrical and thermal conductivity, melting temperature, electrochemical equivalent etc. Electro-discharge machining (EDM) is used for machining low alloy steel. The history of EDM Machining Techniques goes as far back as the 1770s when it was discovered by an English Scientist. However, Electrical Discharge Machining was not fully taken advantage of until 1943 when Russian scientists learned how the erosive effects of the technique could be controlled and used for machining purposes. When it was originally observed by Joseph Priestly in 1770, EDM Machining was very imprecise and riddled with failures. Commercially developed in the mid-1970s, wire EDM began to be a viable

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technique that helped shape the metal working industry we see today. In the mid-1980s.The EDM techniques were transferred to a machine tool. This migration made EDM more widely available and appealing over traditional machining processes. 1.3 Classification of EDM Mainly, there are two dissimilar kinds of EDM: Die-sinking EDM and Wire-cut EDM 1.3.1 Die-sinking EDM In the Sinker EDM Machining process, two metal parts submerged in an insulating liquid are connected to a source of current which is switched on and off automatically depending on the parameters set on the controller. When the current is switched on, an electric tension is created between the two metal parts. If the two parts are brought together to within a fraction of an inch, the electrical tension is discharged and a spark jumps across. Where it strikes, the metal is heated up so much that it melts. Sinker EDM, also called cavity type EDM or volume EDM consists of an electrode and work piece submerged in an insulating liquid such as, more typically, oil or, less frequently, other dielectric fluids. The electrode and work piece are connected to a suitable power supply. The power supply generates an electrical potential between the two parts. As the electrode approaches the work piece, dielectric breakdown occurs in the fluid, forming a plasma channel, and a small spark jumps.

Figure1.3: Schematic setup diagram of Electric Discharge Machining [14] These sparks usually strike one at a time because it is very unlikely that different locations in the inter-electrode space have the identical local electrical characteristics which would enable a spark to occur simultaneously in all such locations. These sparks happen in huge numbers at seemingly random locations between the electrode and the work piece. As the base metal is eroded, and the spark gap subsequently increased, the electrode is lowered automatically by the machine so that the process can continue uninterrupted. Several hundred thousand sparks occur per second, with the actual duty cycle carefully controlled by the setup parameters. 1.3.2 Wire-cut EDM Wire-cut EDM is typically used to cut plates as thick as 300mm and to make punches, tools, and dies from hard metals that are difficult to machine with other methods. Wire EDM also called electric discharge wire cutting process used for producing two or three dimensional complex shapes using an electro thermal mechanism for eroding the material from a thin single stranded by guide rulers‟ metal wire surrounded by de ionized water which is used to conduct electricity. Any hard material can cut by wire EDM process, but the material should have an electrical conductive properties.

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Figure 1.4: Schematic diagram of working of wire-EDM [10] The electrode wire is commonly made of brass or copper material. The diameter range of wire is 0.5 to 0.25 mm. The wire is wound on a two wire spool which is rotated in the same direction to strand the wire. The speed of wire movement is up to 3 m/min. The spark is generated between moving electrode wire and the work piece, thereby removing the material. The dielectric is localized rather than submerging the whole work-piece. It is utilizing CNC controlled machine set up to process the machining operation. 1.3 Machining Parameters of EDM According to the literatures surveyed the following machining parameters are important for EDM [ 1-161] (a) Spark On-time (pulse time or Ton): It is the duration of time expressed in micro seconds in which the peak current is ready to flow in every cycle. This is the time in which energy removes the metallic particles from the work piece. This energy is really controlled by the peak current and the length of the on-time. (b) Spark Off-time (pause time or Toff ): It is the period of time expressed in micro seconds between the two pulse on time. This time permits the melted particle to coagulate on to the work piece and to be wash away by flushing method of the arc gap. (c) Arc gap: It is gap between the electrode and work piece in which the spark generate for eroding the metal from the work piece. It is very thin gap in the range of 10 – 125 μm. (d) Discharge current (Ip): Current is measured in ampere (A). Discharge current is responsible directly for material removal. It contains energy for melting and evaporation. (e) Duty cycle (τ): It is a percentage of the on-time relative to the total cycle time. Thisparameter is calculated by dividing the on-time by the total cycle time (on-time pulse off-time). (f) Voltage (V): It is a potential that can be measure by volt it is also effect to the materialremoval rate and allowed to per cycle. Voltage is given by in this experiment is 50 V. (g) Diameter of electrode (D): It is the diameter of electrode or tool material. Diameter of tool is one factor considered on machining. This experiment 10 mm tool diameter is utilized. (h) Over cut: It is a clearance per side between the electrode and the work piece after the marching operation. 1.5 Characteristics/Specification of EDM EDM description by machinery practice, material removal rate and additional purpose that presented in this table no. 1 Table1.1: Specification on EDM

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S.No. 1

Characteristics Mechanism of process

2 3 4

Spark gap Spark frequency Peak voltage across the gap

Range Controlled erosion i.e. melting and evaporation aided by cavitation 10 - 125 μm 200 – 500 kHz 30 - 250 V

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Maximum material removal rate

5000 mm3/min

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Specific power consumption

2-10 W/mm3/min

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Dielectric fluid uses

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Electrode material

9 10

MRR/TWR Materials application

EDM oil, Kerosene and water with Glycol, silicon-based oil, de ionized water, hydrocarbon fluids etc. Copper, Brass, Graphite, Cu-Graphite alloys, Cu-W alloys, Zinc alloys, Tungsten. 0.1-10 mm3/min All electrically conductive metals and alloys can be machined.

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Shape application

Micro-holes for nozzles, thin slots, visionless complex craters.

1.6 Dielectric fluid: In EDM, as has been discussed earlier, material removal mainly occurs due to thermal evaporation and melting. As thermal processing is required to be carried out in absence of oxygen so that the process can be controlled and oxidation avoided. Oxidation often leads to poor surface conductivity (electrical) of the work piece hindering further machining. Hence, dielectric fluid should provide an oxygen free machining environment. Further it should have enough strong dielectric resistance so that it does not breakdown electrically too easily but at the same time ionize when electrons collide with its molecule. Moreover, during sparking it should be thermally resistant as well. The dielectric fluid is a catalyst conductor, coolant and also a flushing medium. The requirements are:         

The dielectric should have necessary and constant dielectric strength to serve as insulation between the tools and work till the breakdown voltage is reached. It must be de-ionizing quickly afterwards the spark ejection has taken place. It must need little viscosity and a decent moistening ability to provide effective cooling mechanism and remove the swarf particles from the machining gap. It should flush out the particle produce during the spark out of the gap. This is the most important function of the dielectric fluid. Inadequate flushing can result in arcing decreasing the life of the electrode and increasing the machining time. It should be chemically neutral so as not to attack the tool, the job, the movable table or the tank. Its flash point should be high so that there are no fire threats. It should not release any toxic vapors. It should maintain these properties with temperature variation, contamination by working residuals and products of decomposition. It should be economical and easily available.

1.6.1. Properties of dielectric fluids that need to considered while selecting them for operation Dielectric strength: The ability of the fluid to maintain high resistivity before spark discharge and in turn the ability to recover rapidly with a minimal amount of OFF time. Oil with a high dielectric strength will offer a finer degree of control throughout the range of frequencies used. Viscosity: The lower the viscosity of the fluid the better is the accuracy and finishes that can be obtained. In mirror finishing or close tolerance operations, spark gaps can be as small as 0.005 or less. With such tight, physical restrictions such as this, it is much easier to flush small spark gaps with lighter and thinner oil. Specific gravity: is the “weight” of a substance measure by a hydrometer. The “lighter” the oil or lower its specific gravity, faster the heavier particles (chips) settle down. This reduces the gap contamination and possibilities of secondary discharge and/or arcing.

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Color: All dielectric oils will eventually darken with use, but it seems only logical to start with a liquid that is as clear as possible to allow viewing of the submerged part. Clear or “water-white” should be your choice, because any fluid that is not clear when brand new certainly contains undesirable or dangerous contaminants. Odour : The oils that have a strong odour give an indication for the presence of sulfur which is undesirable in the EDM process. Polarity: In EDM, polarity describes which side of the spark gap is positive or negative. Polarity can effect speed, finish, wear, and machining stability. Spark erosion machines can use both positive and negative polarity, depending upon the particular application, but most operations are performed using a positive electrode. Positive polarity will remove material more slowly than negative polarity, but is most of the time to protect the electrode from excessive wear. Negative polarity is used for high-speed metal removal when using graphite electrodes, and should be used when machining carbides, titanium, and refractory metals using copper electrodes. Negative electrodes polarity is sometimes used with copper electrodes when no other method is as successful. With graphite electrodes, negative polarity is much faster than positive polarity by as much as 50% or more, but with as much as 30% to 40% electrode wear. Wire EDM machines generally run with negative polarity – that is the wire is negative and the work-piece is positive. In spark EDM applications, electrode wear is not a consideration as metal removal rates are higher using negative polarity. However, if the wire is burned deep enough, usually about 20% of its diameter, it can no longer withstand the tension and will break. Increasing the speed of the wire will reduce the severity of the wire erosion and help eliminate wire breakage, at the small expense of increased wire consumption. The experimentation has been done by using commercial grade of EDM oil whose specific gravity= 0.763, freezing point= 94ºC used as a catalyst liquid. It is recycled for each experiment by pump. It is works as a coolant and intermediate carrier of molecules between work piece and tool during spark erosion process. 1.7 Flushing method Flushing is the most important function in any electrical discharge machining operation. Flushing is the process of introducing clean filtered dielectric fluid into the spark gap. There are a number of flushing methods used to remove the metal particles efficiently such as pressure flushing, side flushing, and suction flushing. In this experiment we are using side flushing to clean the small gap.

Fig. 1.5.Electrodes shapes for basic types of flushing methods [3]. 1.8. Tool Material Tool material should be such that it would not undergo much tool wear when it is impinged by positive ions. Thus the localized temperature rise has to be less by tailoring or properly choosing its properties or even when temperature increases, there would be less melting. Further, the tool should be easily workable as intricate shaped geometric features are machined in EDM. Thus the basic characteristics of electrode materials are:  

High electrical conductivity – electrons are cold emitted more easily and there is less bulk electrical heating. High thermal conductivity – for the same heat load, the local temperature rise would be less due to faster heat conducted to the bulk of the tool and thus less tool wear.

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

3. Higher density – for the same heat load and same tool wear by weight there would be less volume removal or tool wear and thus less dimensional loss or inaccuracy.  High melting point – high melting point leads to less tool wear due to less tool material melting for the same heat load.  Easy manufacturability.  Cost – cheap. The followings are the different electrode materials which are used commonly in the industry, Keeping in mind technical and economic consideration various material that can be used as tool. In this experiment circular and square shaped Copper tool with side flushing system is used. Table1.2. Different electrode material [7] Material

MRR

TWR

Cost

Copper

High

Low

High

Tungsten

Low

Lowest

High

Brass

High

High

Low

Copper graphite

High

Low

High

Steel

Low

High

Low

Zinc alloys

High

High

Low

Cast iron

Low

Low

Low

1.9. Work piece material In this experiment Low Alloy Steel material is chosen for conducting the experiment. Low alloy steel is a type of steel that has other materials added to it, but the other materials typically make up a small amount of entire steel. Steel commonly is an alloy consisting of carbon and iron, but low alloy steel often adds hard metals such as nickel and chromium. Such metals are classified as high strength, low alloy steel. Perhaps the most well-known alloy steel is stainless steel. This is a steel alloy with a minimum of 10% chromium content. These alloys can, in the right combination, improve corrosion resistance and influence the steel's response to heat treatment. Generally, carbon is the most important commercial steel alloy. Increasing carbon content increases hardness and strength and improves hardenability. Low alloy steels are steels that exhibit mechanical properties superior to the properties of plain carbon steels due to the additions of alloying elements like nickel, chromium, and molybdenum. Total alloy content in these steels may from 2.01 % up to the levels just below those of stainless steels which contain a minimum of 10 % of Chromium. In most of the low alloy steels, the primary function of the alloying elements is to increase hardenability so as to optimize the mechanical properties and toughness after heat treatment. However in some cases the addition of alloying elements is done to reduce environmental degradation for specified service conditions. 1.10. Application of EDM a)

The EDM process is most widely used by the mould-making tool and die industries, but is becoming a common method of making prototype and production parts, especially in the aerospace, automobile and electronics industries in which production quantities are relatively low. b) It is used to machine extremely hard materials that are difficult to machine like alloys, tool steels, tungsten carbides etc. c) It is used for forging, extrusion, wire drawing, thread cutting. d) It is used for drilling of curved holes. e) It is used for internal thread cutting and helical gear cutting.

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f)

It is used for machining sharp edges and corners that cannot be machined effectively by other machining processes. g) Higher Tolerance limits can be obtained in EDM machining. Hence areas that require higher surface accuracy use the EDM machining process. h) Ceramic materials that are difficult to machine can be machined by the EDM machining process. i) Electric Discharge Machining has also made its presence felt in the new fields such as sports, medical and surgical, instruments, optical, including automotive R&D areas. j) It is a promising technique to meet increasing demands for smaller components usually highly complicated, multi-functional parts used in the field of micro-electronics. 1.11 Advantages of EDM a) Any material that is electrically conductive can be cut using the EDM process. b) Hardened workpieces can be machined eliminating the deformation caused by heat treatment. c) X, Y, and Z axes movements allow for the programming of complex profiles using simple electrode. d) Complex dies sections and molds can be produced accurately, faster, and at lower costs. Due to the modern NC control systems on die sinking machines, even more complicated work pieces can be machined. e) The high degree of automation and the use of tool and work piece changers allow the machines to work unattended for overnight or during the weekends f) Forces are produced by the EDM-process and that, as already mentioned, flushing and hydraulic forces may become large for some work piece geometry. The large cutting forces of the mechanical materials removal processes, however, remain absent. g) Thin fragile sections such as webs or fins can be easily machined without deforming the part. 1.11 Limitation of EDM a) Both the material the tool and work piece material has to be electrical conductivity property. Because of this property creation of electric discharges is possible. b) Sometimes the wear rate on the electrode or tool is higher which requires use of more than one tool to finish the machining on the work piece. c) Sometimes the measurement of thin gap between the tool and work piece is not easily predictable especially in case of complex geometries which demands the flushing method to be differ from the simple one. d) Optimum machining settings of the EDM process largely be influenced by on the grouping of the tool and work piece. EDM manufacturers only fund these settings of the required material combination. Therefore skill personnel required to develop his own technology. e) In case of die sinking EDM the cavity formed on the work piece with low metal removal rate. In case of wirecut EDM only outline of the required shape on the work piece has to be machined. Therefore EDM is limited to small production applications. Electrical Discharge Machining (EDM) is a controlled metal-removal process that is used to remove metal by means of electric spark erosion. In this process an electric spark is used as the cutting tool to cut (erode) the work piece to produce the finished part to the desired shape. The metal-removal process is performed by applying a pulsating (ON/OFF) electrical charge of high-frequency current through the electrode to the work piece. This removes (erodes) very tiny pieces of metal from the work piece at a controlled rate. 1.12 Aim of the present investigation: From the research papers in this classification, it is observed that few works has been reported on EDM on the material AlSic, EN-19, SKH 57, AISI H13, AISI D2 tool steel, and various composite materials. Study on EDM of different material and different mathematical model can be used to validate the experimental results. The prime objective of this study is to estimate the material removal rate, surface roughness and overcut of AISI 304 SS with copper tool. The objective of the present work is an attempt to finding feasibility of machining low alloy steel using Square and Circular shapes copper electrode with side flushing. The machining parameter selected for discharge current, pulse on time, and diameter of the tool using Taguchi design approach analyzing the responses MRR and TWR. [1]. To investigate the effect of the machining variables viz. discharge current, pulse on time and voltage on output performances such as MRR, TWR during machining of low alloy steel work piece by using Square and Circular copper tool material. [2]. To derive optimization of machining variables analyzing by Taguchi method.

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2.0

LITERATURE REVIEW

Extensive literature survey has been carried out to study the parametric effect of EDM. Some selected research papers have been discussed related to Electrical Discharge Machining. The studies carried out in these papers are mainly concerned with the EDM parameters such as current, voltage, pulse on time, duty cycle, etc. and how these affect the machining characteristics like MRR, TWR, SR, OC, etc. Tomadi et al. [1] studied the effects of operating parameters of tungsten carbide on the machining characteristics such as surface quality, material removal rate and electrode wear rate. The study was carried out on the basis of the parameters such as pulse on time and pulse off time peak current, power supply voltage,. The investigated of surface quality was in this carried out by using perthometer machine. Material removal rate (MRR) and electrode wear (EW) in this experiment was calculated by using mathematical method. Ojha et al. [2] Studied that EDM researchers have find number of ways to optimize and improve the MRR depart from the traditional EDM sparking phenomenon. During investigation he concluded that, in EDM process Material removal rate (MRR) is an important performance measure. Method of its manufacturing and Electrode design also affect on the cost of electrode. Design of electrode is explored by many researchers and devised various ways of manufacturing. For improving and optimizing performance measures and reducing time and cost of manufacturing. It was observed that the performance of the process, to a large extent, depends on the material, design and manufacturing method of the electrodes explain Jha et al. [3]. Shabgard et al. [4] found the influence of Input Parameters such as pulse on-time and pulse current on the EDM Process. The studied process characteristics included machining features, embracing material removal rate, tool wear ratio, and arithmetical mean roughness, as well surface integrity characteristics comprised of the thickness of white layer and the depth of heat affected zone of AISI H13 tool steel as work piece.Singh et al. [5] have elaborated that the presence of metal partials in dielectric fluid changes its properties, which reduces the insulating strength of the dielectric fluid and increases the spark gap between the tool and work piece. In their study they found that, the process becomes more stable and metal removal rate (MRR) and surface finish increases. Alvi et al. [6] studied the effects of process parameters i.e. discharge current, pulse on and off times, and capacitance on process outputs i.e. material removal rate and electrode wear rate which was determined on the bases of minimum number of experiments. For the prediction, mathematical modeling of process has been done using response surface methodology. In their results a developed model can achieve reliable prediction of experimental results within acceptable accuracy. The performance of the process, to a large extent, depends on the Electrode material, work piece material manufacturing method of the electrodes according to Nikhil et al. [7]. They optimize that a silver electrode give better performance in certain characteristics but the cost become high for machining so keeping in mind cost and other some characteristics a graphite electrode is more preferable than copper electrode in case of both MRR and TWR. Finally they conclude that a suitable selection of electrode can reduce the cost of machining. Singh et al. [8] studied the effects of pulse on and pulse of time machining of AISI D3 die steel using copper and brass electrode in EDM. They compared the material removal rate achieved using different tool materials. Work piece used is AISI D3 and tool materials used copper and brass electrode with pulse on/pulse off as parameter. The electrolyte they used is kerosene oil.The unwanted material from the parent metal is removed through melting and vaporizing by pulse discharge occurs in a small gap between the work piece and the electrode Singh et al. [9] studied Electric discharge machining is an electro sparking method of metal working involving an electric erosion effect. A neural network model and simulated annealing algorithm have been formulated in order to predict and optimize the surface roughness and cutting velocity of the WEDM process in machining of SUS 304 stainless steel materials. The cutting speed and surface roughness of EDM process have been modeled through the response surface methodology and artificial neural networks (ANNs). Kumar et al. [10] reviewed the research is oriented on newer aspects of wire EDM in the field of analysis and optimization. The mathematical models have been developed to predict material removal rate and surface finish while machining AISID2 tool steel at different machining conditions. Nipanikar[11] studied the cutting of D3 Steel material using electro discharge machining (EDM) with a copper electrode by using Taguchi methodology. He used this method to formulate the experimental layout, to analyze the effect of each parameter on the machining characteristics, and to predict the optimal choice for each EDM parameter such as peak current, gap voltage, duty cycle and pulse on time. He found that these parameters have a significant influence on machining

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characteristic such as material removal rate (MRR), electrode wear rate (EWR), radial overcut (ROC). The analysis using Taguchi method reveals that, in general the peak current significantly affects the MRR, EWR and ROC. Flexible machine controller is suggested for Die Sinking EDM to enhance the machining characteristics by Pawade et al. [12]. They evaluated the improvement of machining characteristics of die-sinking EDM such as Material Removal Rate, Surface Roughness and Tool Wear Ratio. He reviewed various techniques which is reported by EDM researchers for improving the machining characteristics have been categorized as process parameters optimization, multi spark technique, powder mixed EDM, servo control system and pulse discriminating. Prajapati et al. [13] studied the effects of process parameters like Pulse ON time, Pulse OFF time, Voltage, Wire Feed and Wire Tension on MRR, SR, Kerf and Gap current on wire EDM by conducting an experiment. For optimization and performance, response surface methodology is used.Similarly, Bergaley et al. [14] optimized the Electrical and Non Electrical Factors in EDM for Machining Die Steel Using Copper Electrode. In their study both the electrical and nonelectrical factors has been focused which governs MRR, EWR and there optimization. The study was based on Design of experiment and optimization of EDM process parameters. The technique used is Taguchi technique which is a statistical decision making tool helps in minimizing the number of experiments and the error associated with it. The research showed that the peak current has significant effect on material removal rate. Daneshmand et al. [15] studied on the basis of results obtained for surface roughness indicates that pulse on time and off time have the highest impact on the surface roughness of NiTi alloy. Taguchi‟s method for the design of experiments, L18 orthogonal array and the „Minitab‟ software program has been used. The experiments indicate that the parameters of discharge current, voltage, and pulse on time have a direct impact on material removal rate (MRR), and with their increase, MRR increases as well. Tool wear rate (TWR) diminishes with the increase of pulse off time and discharge current. On the same line Chikalthankar et al. [16] found the influence of operating parameters like current, voltage, pulse-on time and pulse-off time for responses such as Material Removal Rate (MRR) and Surface Roughness (Ra) on the EDM of WPS DIN 1.2379/AISI D2 tool steel using the copper electrode material. Design of experiment is conducted with L9 orthogonal array and Multi- objective optimization is carried out with the help of Response surface methodology to optimize both the responses at the same time and it was found that current is the more influential parameter affecting the material removal rate and surface roughness. Kumar [17] studied the Status of recent developments and research issues of electrical discharge machining (EDM).The EDM process involves a controlled erosion of electrically conductive work piece by the introduce of rapid and repetitive spark discharge between the tool and work piece by the use of dielectric medium. It is used for machining of parts of aerospace, automobile, nuclear and surgical industry. EDM is also used for the machining of thin and fragile parts.Sandeep [18] studied the process which involves a controlled erosion of electrically conductive materials by the initiation of rapid and repetitive spark discharges between the tool and work piece separated by a small gap of about 0.01 to 0.50. This gap is either flooded or immersed in a dielectric fluid. This study is mainly focused on aspects related to surface quality and metal removal rate which are the most important parameters from the point of view of selecting the optimum condition of processes as well as economical aspects. Singh et al. [19] studied that the enormous Research has been done during the last few years in the field of wire EDM, to increase metal removal rate, tool life, and surface finish and to minimize the time consumed for the process. WEDM is now growing as an important process in various fields; work has been done to use the technology for fabricating micro components.Majhi et al. [20]optimize the approach for the determination of the optimal process parameters which maximize the material removal rate and minimize surface roughness & the tool wear rate by using The input parameters of electrical discharge machining considered for this analysis are pulse current (Ip), pulse duration (Ton) & pulse off time (Toff). On the basis of optimization results it has been found that pulse current (Ip) of 5A, a pulse duration (Ton) of 60μs & pulse off time (Toff) 45μs, which are the best combination of this analysis. Mishra et.al [21] studied that EDM technology is increasingly being used in tool, die and mould making industries, for machining of heat treated tool steels and advanced materials (super alloys, ceramics, and metal matrix composites) requiring high precision, complex shapes and high surface finish. This can be achieved by series of recurring electrical discharges between a cutting tool acting as an electrode and a conductive work piece, in the presence of a dielectric fluid. Further, Chhaniyara1 et al. [22] reviewed work related to EDM and ECM processes applied to stainless steel materials such as AISI 304, AISI 302B, 316 L and 17-4 PH. The non-contact machining technique has been continuously evolving from a mere tool and die making process to a micro-scale application machining alternative attracting a significant amount of research interests

11

and Electrochemical machining (ECM) offers several special advantages including higher machining rate, better precision and control, and a wider range of materials that can be machined. Reddy et al. [23] investigate the Mathematical Modeling of Process Parameters on Material Removal Rate in EDM of EN31 Steel Using RSM Approach. The effect of process parameters namely peak current, pulse on time, duty factor and supply voltage on material removal rate during electrical discharge machining process using response surface methodology. It is found that peak current, pulse on time, duty factor and supply voltage and few of their interactions have significant affect on material removal rate. The adequacy of the model is satisfactory as R² is 98.17% and R² (adj) is 97.59%.Chandramouli et al. [24] also investigated the optimal process parameters of Electric Discharge Machining on RENE80 nickel super alloy material with aluminum as a tool electrode. The input parameters considered are current, pulse on time and pulse off time are used for experimental work and their effect on Material Removal Rate, Tool Wear Rate and Surface Roughness. The Taguchi method is used to formulate the experimental layout, ANOVA method is used to analysis the effect of input process parameters on the machining characteristics and find the optimal process parameters of Electric Discharge Machining. Choudhary et al. [25] studied the effect of pulse-on time, pulse-off time, gap voltage, open voltage, servo voltage, discharge current; polarity, pulse width, duty factor, gas or air pressure, electrode rotation speed on Material removal Rate (MRR), Surface Roughness (Ra) and Tool Wear Rate (TWR). They highlighted that development of Dry EDM Technology enhances the performance parameters such as material removal rate (MRR), Low tool wear rate (TWR), thin recast layer. Shrivastava et al.[26]deliberated the influence of process parameters and electrode shape configuration on the machining characteristics such as surface quality, material removal rate and electrode wear. In their study they found better machining performance is obtained generally with the electrode as the cathode and the work-piece as an anode. To achieve high MRR main process parameters are peak current, pulse on time ,pulse off time, whereas for electrode wear are mainly influenced by peak current and pulse on time. Surface quality is mainly influenced by peak current. As far as tool shape configuration concerned best tool shape for higher MRR and lower TWR is circular, followed by square, triangular, rectangular, and diamond cross sections. Banker et al. [27] considered parameter optimization of Electro Discharge Machine of AISI 304 Steel by using Taguchi Method for design of experiments with three input parameters and their three levels using L9 array. The dielectric used is kerosene diluted with water. The main objective of the research is the analysis to optimize the process parameters of EDM with the help of Taguchi method and using Minitab software in terms of MMR. The research findings show that the copper having high material removal rate with respect to other material such as aluminum, gun metal, brass, etc. Dhakry et al. [28] optimized process parameters in Electro-Discharge Machining (EDM) of tungsten carbide using copper electrodes to development machining mode based on taguchi techniques by using input parameters discharge current (Amp), pulse-on time (μs), duty cycle (%), and gap voltage (Volt) were selected to assess the EDM process performance in terms of material removal rate (MRR: g/min) has been used to design and examine the experiments. They found the MRR increases by selecting higher discharge current and higher duty cycle which capitals providing greater amounts of discharge energy inside gap region. Sanghani et al. [29] studied the Improvement and Optimization of Performance Measures for Electrical Discharge Machining by using machining parameters such as pulse on time, pulse off time, discharge current, gap voltage, flushing pressure, electrode material, etc. of this process should be selected such that optimal value of their performance measures like Material Removal Rate (MRR), Surface Roughness (SR), Electrode/Tool Wear Rate (EWR/TWR), dimensional accuracy, etc. can be obtained or improved. Patil et al. [30] experimented to optimize process parameters in wire-edam using response surface methodology approach for maximizing the material removal rate in wire electrical discharge machining. Abulais et al. [31] studied the Current Research trends in Electric Discharge Machining (EDM). He reviewed the research trends in EDM on ultrasonic vibration, dry EDM machining, EDM with powder additives, and EDM in water. Parts of aerospace, automotive industry and surgical components can be finished by EDM. Singh et al. [32] Optimized Process Parameters of ED whose machining performance is generally evaluated on the basis of Material Removal Rate (MRR), Tool Wear Rate (TWR), Relative Wear Ratio (RWR) and Surface Roughness (SR). This study presented a review of development done in the optimization of EDM related process parameters.Rathi et al. [33] deliberated on Effect of Powder Mixed dielectric in EDM of Inconel 718. in relation to obtain the optimal process parameter combination, optimization is carried out by the Signal-to-Noise (S/N) ratio analysis of Taguchi method using L18 Orthogonal Array was conducted in which they cite that current carrying capacity of any material depends on it electric conductivity and Graphite having highest electric conductivity than Aluminum oxide and Silicon carbide MRR is higher in case of Graphite powder and TWR is less.Prasad et al. [34] studied Taguchi approach for conducting experimentation. Their experiments were designed using L9 orthogonal array considering three process parameter such as, Current, Pulse-On Time, Pulse-Off

12

Time, the response of the process such as Material removal rate (MRR), Tool wear rate (TWR), Surface roughness (RaPrajapati et al. [35 reviewed parameter optimization of electro discharge machine by using Taguchi method, for design of experiments with three input parameters and their three levels using L9 orthogonal array. Thy done 9 experiments with the tool material copper and work piece material AISI 304. The dielectric used is kerosene diluted with water. The objective of the analysis is to optimize the process parameters of EDM with the help of taguchi method and using Minitab software in terms of MRR. Kanekar et al. [36] investigated and optimized EDM performance measures in order to find out best ideal EDM electrode having higher material removal rate, improved surface finish and lower electrode wear rate. For this four EDM electrodes of four different materials (viz. Gr, Cu, Br and Al) are developed by three different manufacturing methodologies. In their research work Vertical Milling Machine, Net Shape Casting and Die Sinking EDM do EDM electrodes fabrication. After the electrode Fabrication testing of electrodes is done on Die Sinking EDM. For optimization two different advanced methods of optimization SAW & TOPSIS are used for analysis of EDM performance measures and to predict optimal choice of each EDM electrode. The analysis of both optimization methods revealed Copper is best EDM electrode followed by Brass, Aluminum and Graphite. Experimental results are provided to verify this approach. Selection of the right dielectric fluid is important for successful operations. Their study presented a literature survey on the various concepts with current research trends and also their effects in electrical discharge machining characteristics as reported by Ramarao et al. [37]. They found that EDM process is basically done through the thermoelectric energy between the work piece and an electrode. In electrical discharge machining (EDM), a process utilizing the removal phenomenon of electrical discharge in dielectric, the working fluid plays an important role affecting the material removal rate and the properties of the machined surface. Modi et al. [38] studied on Optimization of process parameter of EDM for air hardening tool steel. In their study work the rotating tool is used to improve the Metal removal rate (MRR) and to observe its effect on surface finish. They used Taguchi‟s method as a design of experiments and response surface methodology for analysis and optimization. The machining parameters selected as a variables are pulse off time, pulse on time, servo voltage. The output measurement includes MRR and surface roughness. Raut et al. [39] reviewed on Electro Discharge machining (EDM) which is used for machining difficult to machine materials like composites and inter-metallic materials. EDM spark erosion is the same as having an electrical short that burns a small hole in a piece of metal it contacts. In the EDM process both the work piece material and the electrode material just are conductors of electricity. Intricate profiles used in prosthetics, bio-medical applications can be done in EDM. Also Electro Discharge Machining (EDM) find a wide range of applications for production of complicated shapes, micro holes with high accuracy in various electrically conductive materials and high- strength temperature-resistant alloys. Makwana et al. [40] carried out an experimental investigation on AISI 316 stainless steel for tool profile change in die sinking EDM using the taguchi‟s method for design of experiments (DOE). They identified the Optimum electrode shapes in terms of higher MRR, minimum EWR and excellent surface characteristics. The optimum tool shape for higher MRR, lower EWR and excellent SR is circular, followed by rectangular and Triangular cross sections.Lim et al[41] studied on the machining of high-aspect ratio micro-structures using micro-EDM. Pellicer et al [42] emphasized about the tool electrode geometry and process parameters influence on different feature geometry and surface quality in electrical discharge machining of AISI H13 steel. Shabgard et al [43] applied Fuzzy approach to select machining parameters in electrical discharge machining (EDM) and ultrasonicassisted EDM processes. Similarly Ho & Newman [44] state on the art of electrical discharge machining. Mahto and Kumar [45] outline the Taguchi optimization methodology, which is applied to optimize cutting parameters in end milling operation. The study was conducted in machining operation in hardened steel DIN GX40CRMOV5-1. Their results show that the optimum parameters of machining by CNC Milling Machine for specified hardened steel material is obtained at a cutting speed of 355m=min; feed rate 0.1mm per tooth and depth of cut 0:5mm.Lee, et al[46], Marafona et al [47] Maradia et al [48], Song et al [49],, Liu et al [50], Song et al [51] and Kunieda et al [52] have worked on advancing EDM through Fundamental Insight into the Process and new method of optimizing material removal rate using EDM Weng et al to Manoharet al [53-69] have explicitly presented about various parameters and optimizing EDM process. Mahto and Kumar and many others [70-80] have worked on the optimization of process parameters and analyses have been carried out through mathematical analysis tool ANOVA and signal to noise ratio. During the year 2009 to 2015 many significant works have been carried out on non conventional machining process in which EDM was one of the important topic [81-115] Following are the significant observations from survey of literatures (116-161), which have been summarized.

13

From the study of research papers on Electro discharge machining, it is seen that for improving MRR, TWR and surface finish, different modifications are implemented on conventional EDM and they are found beneficial. Some are:               3.0

Experimental research was done to improve surface finish and efficiency by changing parameters. Adapted tool wear compensation was done by using on line prediction of tool wear. Transistor type isopulse generator was integrated with conventional R.C. pulse generator to improve MRR. Response surface methodology was used to plan and analyze the experiments. Theoretical model was developed for developing tool path for generating a desired work piece profile. Multi stage planetary strategies were developed for improving EDM process. Design adaption system (DASMT) was used for making tools. Fuzzy logic analysis coupled with Taguchi method was applied to optimize precision and accuracy. Investigation was done on reduction of tool electrode wear in micro EDM. EDM adaptive control system was developed which automatically regulate tool downtime. Multi attribute decision making was applied on green EDM. A simulation and modeling with new contribution was presented. Research trends were reviewed in Dry EDM, Powder EDM and Ultrasonic Vibration EDM. Planning of EDM process was done to reduce the electrode wear problem. METHODOLOGY OF EXPERIMENTATION

For carrying out the experiments, a numerical control programming electrical discharge machine (EDM) was used to conduct Experiments which has following specifications.  Machine model (ELEKTRA EMS-5535 R50) (die-sinking type) with servo-head (constant gap).  Table Size – 550mm x 350mm ,  Movement – X 300, Y 200, Z 250mm.  Maximum weight carrying capacity of Job – 300 Kg.

Fig. 3.1: Die Sinker EDM machine setup with tool and work piece (Model: ELEKTRA EMS-5535 R50) The ELEKTRA EMS has the provisions of programming in the Z-vertical axis-control and manually operating X and Y axes. In this work, conductive metal matrix composite AISI 304 SS was selected as the work piece material. Four different volume fraction percentages (5, 10, 20 and 25) of silicon carbide in the aluminum matrix were chosen. The present experiments have been performed using copper electrodes (99.7% Cu, 0.12% Zn, 0.02% Pb, 0.02% Sn) with positive polarity. The electrode used is 15 mm in diameter and 50 mm in height. Commercial kerosene was used as a dielectric fluid. The machining was generally carried out for a fixed time interval and the amount of metal removed was measured by taking the difference in weights of the work piece before and after electrical discharge machining. Material removal rate (MRR) in mm3/min and electrode wear ratio (EWR) can be calculated by the following formulae:

14

…Eqn (1)

…Eqn (2)

…Eqn (3) where,      

VEW is the volumetric electrode wear in mm3/min, ww is the work piece weight loss in gms, we is the electrode weight loss in gms, ρw is the work piece material density in gm/cm3, ρe is the electrode material density in gm/cm3 and T is the machining time in min.

The surface roughness (Ra) of each machined work piece was measured using the Mitutoyo Talysurf (SJ – 201). Each experiment was repeated three times for better results and the average was calculated. For measuring the gap size, the diameter of the resulted hole in the work piece block was measured three times at different locations and the average was calculated. Profile projector 10 multiplied by magnification was used to measure these diameters. The gap size (GS) was then calculated by the difference between the radius of the average measured diameter and the radius of the electrode. Weighing machine Precision balance was used to measure the weight of the work piece and tool. This machine capacity is 300 gram and accuracy is 0.001 gram and Brand: SHINKO DENSHI Co. LTD, JAPAN, and Model: DJ 300S.

Fig. 3.2: Sample machine used for Weight Balance 4.0

RESULT AND DISCUSSION

This influences of MRR and TWR findings of the results were analyzed factor wise viz. discharge current, pulse on duration, pulse off duration, is most important with help of Taguchi method. 4.1 Response table The response table for MRR and TWR by using Circular copper tool is shown in Table 4.1 along with the input factors. Table 4.1: The response table for MRR and TWR by using Circular copper tool Experiment NO

IP

T off

Ton

15

SN MRR

MRR

1

1

1

1

-25.4600

0.053333

2 3

1 1

1 1

2 3

-24.8066 -25.1435

0.0575 0.055312

4

1

2

1

-23.6941

0.065357

5

1

2

2

-23.3309

0.068148

6

1

2

3

-22.9092

0.071538

7

1

3

1

-23.1940

0.069231

8

1

3

2

-23.1459

0.069615

9

1

3

3

-22.6154

0.074

10

2

1

1

-20.5993

0.093333

11 12

2 2

1 1

2 3

-19.4076 -13.4588

0.107059 0.212353

13

2

2

1

-18.7108

0.116

14

2

2

2

-17.4857

0.133571

15 16

2 2

2 3

3 1

-16.2402 -17.6262

0.154167 0.131429

17

2

3

2

-17.5323

0.132857

18

2

3

3

-16.7957

0.144615

19

3

1

1

-14.5787

0.186667

20

3

1

2

-12.7184

0.23125

21

3

1

3

-11.7484

0.258571

22 23

3 3

2 2

1 2

-13.6075 -12.9082

0.20875 0.22625

24

3

2

3

-11.7005

0.26

25

3

3

1

-13.6075

0.20875

26

3

3

2

-12.1914

0.245714

27

3

3

3

-7.6390

0.415

4.2 Influences on MRR The S/N ratios for MRR are calculated as given in Equation 4.1. Taguchi method is used to analysis the result of response of machining parameter for larger is better criteria. LB : η = 10 log [ 1/n ∑yi-2]…………………..(4.1)

n

I=1 Where,  η denotes the S/N ratios calculated from observed values,  yi represents the experimentally observed value of the i th experiment and  n=1 is the repeated number of each experiment in L-27 OA is conducted. The analysis of variances for the factors is shown in Table 4.2 which is clearly indicates that the T off is not important for influencing MRR and Ip and Ton are the most influencing factors for MRR and as well as the interaction Ip x Ton is significant. The delta values are Dia. of tool, Ton and Ip are 1.1493, 15.0841 and 18.3901 respectively, depicted in Table 4.3. The case of MRR, it is “Larger is better”, so from this table it is clearly definite that Ip is the most important factor then Ton and last is dia. of the tool. Table 4.2 Analysis of Variance for MRR, using Adjusted SS for Tests Source

DF

Seq SS

Adj SS

16

Adj MS

F

P

IP

2

0.155114

0.155114

0.077557

56.09

0.000

T off

2

0.003448

0.003448

0.003448

1.25

0.338

T on

2

0.015622

0.015622

0.007811

5.65

0.030

IP*T off

4

0.004541

0.004541

0.001135

0.82

0.547

IP*Ton

4

0.008898

0.008898

0.002224

1.61

0.263

T off*Ton

4

4 0.001954

0.001954

0.000489

0.35

0.835

Error

8

0.011062

0.011062

0.001383

Total

26

0.200639

S = 0.0371856 R-Sq = 94.49% R-Sq(adj) = 82.08%

Main Effects Plot for SN ratios Data Means

IP

-12

Ton

-15

Mean of SN ratios

-18 -21 -24 1

2

3

1

2

3

T off

-12 -15 -18 -21 -24 1

2

3

Signal-to-noise: Larger is better

Fig 4.1 Analysis of Variance for MRR (main effect plots of IP, Ton and T Off) (Larger is better) Table 4.3 Response Table for Mean of MRR Level

Ip

1

0.065

2

0.136

3

0.249

Ton

Delta Rank

17

Toff

During the process of Electrical discharge machining, the influence of various machining parameter like Ip, Ton and Toff has significant effect on MRR, as shown in main effect plot for S/N ratio of MRR in Fig 4.1. The discharge current (Ip) is directly proportional to MRR. This is expected because an increase in pulse current produces strong spark, which produces the higher temperature, causing more material to melt and erode from the work piece. Besides, it is clearly evident that the other factor does not influence much as compared to Ip and similar conclusions were shown by Harpreet Singh and Amandeep Singh [8]. But, with increase in discharge current from 3A to 5A MRR increases slightly. However, MRR decreases monotonically with the increase in pulse on time. The regression equation is MRR = 0.186 - 0.0682 IP - 0.0474 T off - 0.0816 Ton + 0.0208 IP*IP + 0.0077 Toff *T off + 0.0130 T on *T on + 0.0122 IP*T off + 0.0264 IP*Ton + 0.00261 T off* Ton Table 4.4: Analyzed Results of TWR T off (µs) 1

Ton (µs) 1

TWR (mm3/min)

SN TWR

1

IP (A) 1

0.000606

64.3497

2

1

1

2

0.000312

70.1030

3

1

1

3

0.000625

64.0824

4

1

2

1

0.001429

56.9020

5

1

2

2

0.000741

62.6067

6

1

2

3

0.000385

68.2995

7

1

3

1

0.000769

62.2789

8

1

3

2

0.000769

62.2789

9

1

3

3

0.0008

61.9382

10

2

1

1

0.002222

53.0643

11

2

1

2

0.001765

55.0666

12

2

1

3

0.001176

58.5884

13

2

2

1

0.005333

45.4600

14

2

2

2

0.001429

56.9020

15

2

2

3

0.001667

55.5630

16

2

3

1

0.003571

48.9432

17

2

3

2

0.000714

62.9226

18

2

3

3

0.002308

52.7364

19

3

1

1

0.026667

31.4806

20

3

1

2

0.015

36.4782

21

3

1

3

0.011429

38.8402

22

3

2

1

0.025

32.0412

23

3

2

2

0.00875

41.1598

24

3

2

3

0.008571

41.3389

25

3

3

1

0.01875

34.5400

26

3

3

2

0.01

40.0000

27

3

3

3

0.003333

49.5424

Experiment NO

Table 4.5: Analysis of Variance for TWR, using Adjusted SS for Tests

18

Source

DF

Seq SS

Adj SS

Adj MS

F

P

IP

2

0.0009764

0.0009764

0.0004882

306.64

0.000

T off

2

0.0000202

0.0000202

0.0000101

6.35

0.022

Ton

2

0.0001859

0.0001859

0.0000929

58.38

0.000

IP*T off

4

0.0000553

0.0000553

0.0000138

8.69

0.005

IP*Ton

4

0.0002320

0.0002320

0.0000580

36.43

0.000

T off*Ton

4

0.0000088

0.0000088

0.0000022

1.38

0.322

Error

8

0.0000127

0.0000127

0.0000016

Total

26

0.0014914

S = 0.00126176 R-Sq = 99.15% R-Sq(adj) = 97.22%

The regression equation is TWR = 0.00045 - 0.00275 IP + 0.00394 T off - 0.00319 Ton + 0.00520 IP*IP - 0.000322 Toff *T off + 0.00198 T on *T on 0.00182 IP*T off - 0.00384 IP*Ton - 0.000032 T off* Ton Main Effects Plot for SN ratios Data Means

IP

T off

Mean of SN ratios

60 50 40 1

2 T on

3

1

2

3

1

2

3

60 50 40

Signal-to-noise: Smaller is better

Fig 4.2 Analysis of Variance for TWR, using Adjusted SS for Tests (main effect plots) Table 4.5: Analyzed Results of MRR Experiment NO

IP

T off

Ton

MRR

SN MRR

1

1

1

1

0.056444

-24.9676

2

1

1

2

0.059318

-24.5362

3

1

1

3

0.06093

-24.3033

19

4

1

2

1

0.067568

-23.4052

5

1

2

2

0.074571

-22.5486

6

1

2

3

0.076286

-22.3511

7

1

3

1

0.081875

-21.7370

8

1

3

2

0.084194

-21.4944

9

1

3

3

0.087667

-21.1433

10

2

1

1

0.115

-18.7860

11

2

1

2

0.142778

-16.9068

12

2

1

3

0.151765

-16.3766

13

2

2

1

0.15125

-16.4061

14

2

2

2

0.160625

-15.8837

15

2

2

3

0.184286

-14.6902

16

2

3

1

0.141667

-16.9746

17

2

3

2

0.15375

-16.2637

18

2

3

3

0.170667

-15.3570

19

3

1

1

0.236

-12.5418

20

3

1

2

0.28

-11.0568

21

3

1

3

0.288889

-10.7854

22

3

2

1

0.236

-12.5418

23

3

2

2

0.242

-12.3237

24

3

2

3

0.291111

-10.7188

25

3

3

1

0.241

-12.3597

26

3

3

2

0.31375

-10.0683

27

3

3

3

0.32125

-9.8631

20

Main Effects Plot for SN ratios Data Means

IP

-10

T off

Mean of SN ratios

-15 -20 1

2

3

1

2

3

Ton

-10 -15 -20 1

2

3

Signal-to-noise: Larger is better

Fig 4.3 Analysis of Variance for IP, T off and Ton (main effect plots) (Larger is better) Table 4.6 Analysis of Variance for MRR, using Adjusted SS for Tests Source

DF

Seq SS

Adj SS

Adj MS

F

P

IP

2

0.182567

0.182567

0.091283

804.63

0.000

T off

2

0.002335

0.002335

0.001167

10.29

0.006

Ton

2

0.005275

0.005275

0.002638

23.25

0.000

IP*T off

4

0.001920

0.001920

0.000480

4.23

0.039

IP*Ton

4

0.002502

0.002502

0.000625

5.51

0.020

T off*Ton

4

0.000486

0.000486

0.000122

1.07

0.431

Error

8

0.000908

0.000908

0.000113

Total

26

0.195992

S = 0.0106512 R-Sq = 99.54% R-Sq (adj) = 98.50%

The regression equation is MRR = 0.0280 - 0.0061 IP + 0.0045 T off - 0.0008 Ton + 0.0197 IP*IP + 0.00109 Toff *T off - 0.00346 T on *T on 0.00049 IP*T off + 0.0141 IP*Ton + 0.00174 T off* Ton Table 4.7 Analyzed Results for TWR Experiment NO

IP

T off

Ton

TWR

SN TWR

1

1

1

1

0.001778

55.0025

2

1

1

2

0.000682

63.3266

21

3

1

1

3

0.000698

63.1269

4

1

2

1

0.001081

59.3228

5

1

2

2

0.000571

64.8608

6

1

2

3

0.000571

64.8608

7

1

3

1

0.00125

58.0618

8

1

3

2

0.000645

63.8066

9

1

3

3

0.001

60.0000

10

2

1

1

0.0105

39.5762

11

2

1

2

0.002222

53.0643

12

2

1

3

0.001765

55.0666

13

2

2

1

0.006875

43.2545

14

2

2

2

0.0025

52.0412

15

2

2

3

0.005

46.0206

16

2

3

1

0.005

46.0206

17

2

3

2

0.006875

43.2545

18

2

3

3

0.002667

51.4806

19

3

1

1

0.036

28.8739

20

3

1

2

0.016667

35.5630

21

3

1

3

0.011111

39.0849

22

3

2

1

0.028

31.0568

23

3

2

2

0.027

31.3727

24

3

2

3

0.015556

36.1623

25

3

3

1

0.035

29.1186

26

3

3

2

0.02875

30.8272

27

3

3

3

0.02125

33.4528

22

Main Effects Plot for SN ratios Data Means

IP

T off

60

Mean of SN ratios

50 40 30 1

2 Ton

3

1

2

3

1

2

3

60 50 40 30

Signal-to-noise: Smaller is better

Fig 4.4 Analysis of Variance for IP, T off and Ton (main effect plots) (Smaller is better) Table 4.8: Analysis of Variance for TWR, using Adjusted SS for Tests Source

DF

Seq SS

Adj SS

Adj MS

F

P

IP

2

0.0028419

0.0028419

0.0014209

181.39

0.000

T off

2

0.0000262

0.0000262

0.0000131

1.67

0.247

Ton

2

0.0002443

0.0002443

0.0001221

15.59

0.002

IP*T off

4

0.0000523

0.0000523

0.0000131

1.67

0.249

IP*Ton

4

0.0002238

0.0002238

0.0000560

7.14

0.009

T off*Ton

4

0.0000690

0.0000690

0.0000172

2.20

0.159

Error

8

0.0000627

0.0000627

0.0000078

Total

26

0.0035201

S = 0.00279881 R-Sq = 98.22% R-Sq(adj) = 94.21%

The regression equation is TWR = 0.0126 - 0.0149 IP - 0.00454 T off + 0.00160 Ton + 0.00782 IP*IP + 0.00053 Toff *T off + 0.00074 T on *T on + 0.00179 IP*T off - 0.00410 IP*Ton CONCLUSION In this investigation the effect of machining outputs taken for consideration are:  material removal rate and tool wear rate of the low alloy steel work piece

23

 Copper Tools used were in square and circular shape  The method was side flushing From the inferences of the experiments conducted, it can be concluded that the surface roughness depends upon various parameters settings such as discharge current (Ip), pulse on time (Ton) and pulse off time (T off). Both these outputs are most significant in industrial applications. Taguchi method with 27 array L-27 OA was performed with the help of Minitab software to analyze the results and theses responses were partially validated experimentally. The following points bring to a close to authenticate that: 1. 2. 3.

MRR result shows that the discharge current is most significant or influencing factor then pulse on time and at last is voltage on the given input. MRR increased linearly to some level due to current increment and decreases slightly with pulse on time. Tool wear is affected by all the three factors studied in which discharge current is the most important factor in tool wear rate which is seconded by pulse on time and lastly by pulse off time.

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