t. rajasekaran and t. ponvel murugan -...

T. RAJASEKARAN AND T. PONVEL MURUGANSchool of Mechanical Engineering, SRM University, Kattankulathur-603203, India

Corresponding author: [email protected],[email protected]

ABSTRACT

There is an increasing demand for industrial products,not only with the increased number of functions and alsothere will be a requirement of product in reduced size.Hence, it is essential to develop a product with maximumfunctions and minimum size. Micromachining technologygives the best solution to develop the product withmaximum number of functions and also the size of theproduct will be in micrometers range. Micromachiningtechnology uses various machining techniques to launchminiaturized products more efficiently and well aheadof their competitors in the market. One of the machiningtechniques involved in micromachining is Micro Electricaldischarge machining (Micro – EDM). Micro – EDM usesthe same working principle as EDM which producesrepetitive discharges of electrical sparks between the gapof tool (electrode) and the work piece.

AISI 1040 steel is a high carbon steel which provides highyield strength and also it is employed in making springmaterials, cutting saws, blades and in micro levelapplications it is used in manufacture of micro grippers,micro actuators. The wear rate is also less compared tothe copper and graphite electrodes employed previouslyin EDM machining.

In this present work, optimization of micro electricaldischarge machining parameters using Taguchi’sapproach is proposed for AISI 1040 steel because of itshigher hardness and also economically feasible to producedies at cheaper cost. Experimentation was planned as perTaguchi’s L9 orthogonal array. Each experiment wasperformed under different machining conditions of gapvoltage, capacitance, feed, and threshold.

Two responses namely material removal rate and surfaceroughness were considered for each experiment. Theoptimum machining parameter combination is obtainedby using the analysis of signal to noise (S/N) ratio. Thelevel of importance of the machining parameters on thematerial removal rate and surface roughness isdetermined by using analysis of variance (ANOVA).Thehighly effective parameters on both the MRR and surfaceroughness are found as gap voltage and capacitance. Thevariation of the MRR and surface roughness withmachining parameters is optimized by using taguchitechnique and gray relational analysis technique with theexperimental values.

Keywords: Micro-EDM, Machining, Micro hole, AISI 1040,Anova

1. INTRODUCTION

Electrical discharge machining (EDM) is a non-traditional concept of machining which has beenwidely used to produce dies and molds. It is alsoused for ûnishing parts for aerospace andautomotive industry and surgical components [1].This technique has been developed in the late 1940s[2]. The EDM process is based on the thermoelectricenergy created between a workpiece and anelectrode submerged in a dielectric ûuid. When theworkpiece and the electrode are separated by aspeciûc small gap, the so-called ‘spark gap’, apulsed discharge occurs which removes materialfrom the workpiece through melting andevaporation. In recent years, numerousdevelopments in EDM have focused on theproduction of micro-features. This has becomepossible due to the availability of new CNC systemsand advanced spark generators that have helpedto improve machined surface quality. Also, the verysmall process forces and good repeatability of theprocess results have made micro-EDM the bestmeans for achieving high-aspect-ratio micro-features [3].

Electrical discharge machining (EDM) enablesto machine extremely hard materials and complexshapes can be produced with high precision.Therefore, EDM is a potential and attractivetechnology for the machining of ceramics,providing that these materials have a sufficientlyhigh electrical conductivity. A maximum electricalresistivity of 100 � cm is seen as a limit [4]. EDMdoes not make direct contact between the electrodeand the workpiece eliminating mechanical stresses,chatter and vibration problems during machining.Today, an electrode as small as 0.1 mm can be usedto ‘drill’ holes into curved surfaces at steep angleswithout drill ‘wander’ [5].

The basis of EDM can be traced as far back as1770, when English chemist Joseph Priestlydiscovered the erosive effect of electrical discharges

134 T. Rajasekaran and T. Ponvel Murugan

or sparks [6]. However, it was only in 1943 at theMoscow University where Lazarenko andLazarenko [7] exploited the destructive propertiesof electrical discharges for constructive use. Theydeveloped a controlled process of machiningdifûcult-to-machine metals by vapourising materialfrom the surface of metal. The Lazarenko EDMsystem used resistance–capacitance type of powersupply, which was widely used at the EDMmachine in the 1950s and later served as the modelfor successive development in EDM [8].

It has also been seen in recent years, rapiddevelopments in the defense industry,communication systems and micro-electro-mechanical systems (MEMS) have led to signiûcantamounts of research in the ûeld of magneticinterference of MEMS and system with micro-structures including micro-shafts, micro-holes,specially shaped micro-holes and micro-slots.Micro-manufacturing technique has increasinglyattracted research interest. Currently micro-holesare formed by differ chemical machining (ECM) andmicro-ultrasonic machining (MUSM). Due to thedifferent working mechanisms, these methods yielddifferent results. Among them manufacturingmethods including micro-EDM, electron beammachining (EBM), and laser machining, etching,and electric. Among them, micro-EDM providesadvantages such as low-cost apparatus, high aspectratio of parts, and the capability of fabricatingcomplex 3D shapes. It is therefore potentiallysuitable for manufacturing micro-holes and micro-parts in miniature devices [9-20].

2. EXPERIMENTAL DETAILS

2.1. Machine Details

DT - 110 integrated multi process micro machinetool developed by Mikro tools Pvt Ltd., was usedfor conducting the experiments and the machinetool is shown in the Fig. 1. It is a 3 – axis automaticmulti – process integrated machining system formicro – machining of a variety of materials, metallicand non – metallic to a very high order of precision.However, with technology moving rapidly towardsthe development of micro devices in the millimeterto sub – millimeter range, demand for more complexminiaturized and high – precision parts isaccelerating. DT – 110, with the capability ofmultiple machining processes and high machineaccuracy (+/- 1 micron) is leading the way. Themaximum travel range of machine is 200mm

(X-axis), 100mm (Y-axis), 100mm (Z- axis) and theresolution is 1µm. In this experiment the micro-EDM setup shown in Fig.2 is used for performingthe experiments. [21].

Figure 2: Micro – EDM Setup

Figure 1: DT-110 Multi Process Micro Machine Tool

2.2. Work Piece, Electrode and Dielectric Fluid

The work piece material used in this study was AISI1040 steel. The standard (ASME) composition ofAISI 1040 steel is given in the Table 1. The electrodematerial used in this study was copper tungsten ofdiameter 300ìm with a length of 70mm. Thedielectric fluid used in this study was commerciallyavailable “Total EDM 3 oil”. The properties of theelectrode and dielectric material are listed in Tables2, 3 respectively.

Surface Roughness and Material Removal Analysis for AISI 1040 Steel in Micro Electric Discharge... 135

Table 1Composition of AISI 1040 Steel (% by Weight)

C Mn Si S P

0.37-0.44 0.60-0.90 0.04 0.05 0.37-0.44

Table 2Properties of Electrode Material

Material CuW

Composition (%) 60%W–40%Cu

Density (g/cm3) 12.6

Hardness (HRB) 77

Thermal conductivity (W/mK) 160

Electrical conductivity (% I.A.C.S) 33

Table 3Properties of Dielectric Fluid

Material EDM oil 3

Volumetric mass at 15 °C (kg/m3) 813

Viscosity at 20 °C (mm2/s) 7.0

Aromatics content (wt. %) 0.01

Auto-ignition temperature (°F) 470

Distillation range, IBP/FBP (°C) 277/322

Flash point Pensky-Martens (°C/°F) 134/259

2.3. Experimental Design

Experiments were carried out by DoE approachusing L9 OA. The input machining parameters suchas gap voltage, capacitance, feed and threshold atthree levels were considered and they wereallocated in L9 OA (Table 4).

Table 4Machining Parameters and their Levels

S. No Control Factor Unit Level 1 Level 2 Level 3

1 Gap voltage V 80 100 120

2 Capacitance pF 10 100 1000

3 Feed µm/s 4 6 8

4 Threshold - 20 40 60

2.4. Equipments used for Measurement

2.4.1. Video Measuring System (VMS)

Video Measuring System is a photoelectricmeasuring system of high precision and efficiency.It is composed of a series of components, such asCCD color camera of high resolution, continuouszoom lens, color monitor, video crosshairsgenerator, precise linear scale, multi-functionalDigit Readout (DRO), 2D measuring software and

high precision work table. In this study the diameterof the micro hole drilled by using micro-EDM wasmeasured by using Video measuring system. Thepicture of video measuring system is shown inFigure 3.

Figure 3

2.4.2. Talysurf CCI Non Contact 3D Profiler

The Talysurf CCI Lite is an advanced type ofmeasurement interferometer. It uses an innovative,patented correlation algorithm to find the coherencepeak and phase position of an interference patternproduced by our precision optical scanning unit.All material types are measurable including glass,liquid inks, photo resist, metal, polymer and pastes.Versatility is one key benefit of the Talysurf CCI.Polished or rough, curved, flat or stepped surfaceswith reflectivity between 0.3% and 100% can all bemeasured using one single algorithm, with no needto change mode for different surfaces and noconcerns about the wrong mode being used. In thisstudy, Talysurf CCI non contact profiler was usedto find out the surface roughness of the micro holesurface. The Talysurf CCI non contact 3D profileris shown in Figure 4 and the optical scanning unitis shown in Figure 5.

Figure 4: Talysurf CCI Non Contact 3D Profiler


3. RESULTS AND DISCUSSION

3.1. Diameter of Micro Hole

The diameter of micro hole was measured by usingvideo measuring system. The image of the microhole obtained in VMS is shown in Fig 6.From theobtained diameter, the MRR was calculated byusing the formula

MRR = Volumeof thematerial removed fromthe workpiece

Timeof machining

two output parameters MRR and surface roughnesswas considered to determine the performance ofmicro-EDM of AISI 1040 steel. Therefore it isnecessary to determine the optimal combination ofthe parameters to be used. The single optimalcombination for multiple output parameters can beobtained by applying the Taguchi Method.

Table 5L9 Orthogonal Array, Machining Parameters and

Observed Values

Ex. Gap Capacit- Feed Thres MRR SRRaNo. Volt- ance (µm/s) hold (10-4 (µm)

age (pF) mm3/(V) min)

1 80 10 4 20 4.42 0.52622 80 100 6 40 4.77 0.49653 80 1000 8 60 5.12 0.34234 100 10 6 60 5.60 0.61355 100 100 8 20 4.77 0.91326 100 1000 4 40 5.47 0.24407 120 10 8 40 6.09 0.33128 120 100 4 60 6.79 0.17629 120 1000 6 20 5.12 0.4150

Figure 5: Optical Scanning Unit

Figure 6: Blind Micro Hole

3.2. Surface Roughness of Micro Hole

The surface roughness of the micro hole wasmeasured by using Talysurf CCI non contact 3Dprofiler. The surface image of the section of a microhole is shown in Fig. 7. From the obtained imagethe non contact profiler uses the Talymap surfaceanalysis software provide the value of surfaceroughness for respective section of micro hole.

3.3. Values of MRR and Surface Roughness

The results of the values of the MRR and surfaceroughness are given in the Table 5. In this study,

Figure 7: Surface Image of Micro Hole

Figure 8: Variation of MRR between Experiments


3.4. Taguchi Method

Taguchi of Nippon Telephones and TelegraphCompany, Japan has developed a method based on“ORTHOGONAL ARRAY” experiments whichgives much reduced “variance” for the experimentwith “optimum settings” of control parameters.Thus the marriage of Design of Experiments withoptimization of control parameters to obtain BESTresults is achieved in the Taguchi Method.“Orthogonal Arrays” (OA) provide a set of wellbalanced (minimum) experiments and Dr.Taguchi’s Signal-to-Noise ratios (S/N), which arelog functions of desired output, serve as objectivefunctions for optimization, help in data analysis andprediction of optimum results.

3.4.1. Calculation on S/N Ratio for MRR

The objective of this study is to maximize thematerial removal rate, therefore the S/N ratio forlarger the better was selected and it is given by� = – 10 log10 (1/yi

2)Where, � - S/N ratio;

Yi – measured value of output parameterThe values obtained by Taguchi method (S/N

ratio with respect to MRR) are given in Table 6.

Table 6S/N Ratio with Respect to MRR

Exp. No. MRR S/N ratio (dB)� = -10 log 10 (1/yi

2)

1 4.20 -47.092 4.98 -46.423 4.71 -45.814 5.27 -45.035 5.19 -46.426 5.14 -45.247 5.52 -44.308 6.54 -43.369 5.44 -45.81

Figure 9: Variation of Surface Roughnessbetween Experiments

(a) At Gap voltage level

(b) At capacitance level

(c) At Feed level

(d) At Threshold level

Figure 10: Main Effects Plot for Means of S/N Ratio for MRR


The values obtained by Taguchi method (S/Nratio with respect to Surface roughness) are givenin Table 7.

Table 7S/N Ratio with Respect to Surface Roughness

Exp. Surface Roughness S/N ratio (dB)No. Ra(µm) � = –10 log10 (yi

2 )

1 4.20 -0.77772 4.98 -0.9243 4.71 -2.1674 5,27 -0.4505 5.19 -0.0156 5.14 -3.7527 5.52 -2.3038 6.54 -5.6859 5.44 -1.458

3.5. ANOVA Analysis

One of the most powerful statistical methods fordata analysis is the method of analysis of variance(ANOVA). It is a statistically based decision toolfor detecting any differences in averageperformance of the group of items tested.

In this study, ANOVA is used to determine thepercentage contribution of the process parametersthat affecting the MRR and Surface roughness. Fromthe means of gray relational grades at differentlevels for the corresponding factors the ANOVAtable was given in Table 8.

Table 8ANOVA Table for AISI 1040

Factors Degrees Sum of Mean F-ratio %of Squares sum of contri-

Freedom Squares bution

Gap Voltage 2 0.8440 0.422 7.482 22.408

Capacitance 2 1.1239 0.56195 9.9636 29.843

Feed 2 0.9408 0.4704 8.3404 24.973

Threshold 2 0.8560 0.428 7.5886 22.721

Error 2 0.1129 0.0564

Total 10 3.3306 100

From the ANOVA table it was observedthat the feed has 26.793% contribution whichis followed by 26.748% of capacitance, 23.412%of gap voltage and 23.082% of threshold.The percentage contribution of the processparameters obtained through ANOVA is shown inthe Figure 13.

(a) At Gap Voltage Level

(b) At Capacitance Level

(c) At Feed Level

(d) At Threshold Level

Figure 11: Main Effects Plot for Means of S/NRatio for Surface Roughness


4. CONCLUSION

In this study, an attempt has been made to find theoptimal combination of process parameters to obtainmaximum material removal rate and minimumsurface roughness using Taguchi technique as wellas Gray relational analysis technique and thepercentage contribution of process parameters andits influence on the output parameters wereinvestigated using ANOVA. It is shown that theoutput parameters namely material removal rate(MRR) and surface roughness are improved in theoptimal combination obtained by Taguchi techniqueand Gray relational analysis technique. The resultswere discussed in detail and from the results, thefollowing conclusions are drawn:

The optimal combination of process parametersfor obtaining maximum MRR through Taguchitechnique for machining AISI 1040 steel usingMicro-EDM is given below:

1. Gap voltage – 80V2. Capacitance – 10nF3. Feed – 8µm/s4. Threshold – 20

The optimal combination of process parametersfor obtaining minimum surface roughness throughTaguchi technique for machining AISI 1040 steelusing Micro-EDM is given below:

1. Gap voltage – 80V2. Capacitance – 1000nF3. Feed – 4µm/s4. Threshold – 20

The optimal combination of process parametersto obtain maximum material removal rate andminimum surface roughness through Grayrelational analysis technique for machining AISI1040 steel using Micro-EDM is A2B3C4D1. i.e.

Figure 12: Percentage Contribution of Machining Parameters

1. Gap voltage – 120V

2. Capacitance – 100nF

3. Feed – 8µm/s

4. Threshold – 60

The percentage contribution and the influenceof process parameters on MRR and surfaceroughness were determined by using ANOVA,which gives the following results:

1. Gap voltage – 23.412%

2. Capacitance – 26.748%

3. Feed – 26.793%

4. Threshold – 23.082%

Finally, it was concluded that the feed has moreinfluence on the surface roughness and materialremoval rate, which is followed by capacitance, gapvoltage and threshold

4.1. Suggestions for Further Study

� Mathematical models are to be constructed forgenerating the results that matches with thepractical experiments.

� Optimization of process parameters usingdifferent electrode materials like CuW, AgWand the performance of the electrode materialsare to be studied.

� Other than material removal rate and surfaceroughness, some other performancecharacteristics like cylindricity of micro hole,roundness of micro hole are to be identified andthe optimal combination is to be determined.

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