Experimental Investigation of Electrochemical Micro Machining Process Parameters on Ti6Al4V by using Simulated Annealing

Experimental Investigation of Electrochemical Micro Machining Process Parameters on Ti6Al4V by using Simulated Annealing P.V. Sreenivasula Reddy 1, A. Sreenivasulu Reddy 2 1 P.G student & 2 Assistant professor Department of mechanical engineering & S.V University Tirupati, A.P, India Abstract Electrochemical Micro Machining (ECMM) is an emerging nonconventional machining technology for producing micro scale components. The micro machining of very hard materials like super alloys, Ti-alloys, Ni-alloys, tool steel, stainless steel, etc. is very difficult with conventional machining. By the use of ECMM the above limitations can be overcome. This paper investigates the effect of process parameters on Overcut and surface roughness and parametric optimization of process parameters in ECMM of Ti6Al4V using Simulated Annealing. Experiments are conducted based on Taguchi s L 16 orthogonal array (OA) with four process parameters viz. applied voltage, duty cycle, feed rate and frequency. Overcut is calculated by measuring the diameter of the hole with Vision measuring system (VMS-10). Surface Roughness is measured using Non-contact Surface Roughness Tester (Talysurf). Analysis of variance (ANOVA) is performed to get the contribution of each parameter on the performance characteristics and it is observed that applied voltage and duty cycle are the significant process parameters that affect the responses overcut and surface roughness respectively. Keywords ECMM, Taguchi s L 16 OA, Ti6Al4V, Surface Roughness, Overcut, ANOVA and Simulated Annealing. I. INTRODUCTION Now-a-days, micro manufacturing techniques find wider application in various industries like electronic, semi-conductors, medical, aerospace, naval and ultraprecision machines. The shaping of parts with dimensions in the range of 5 to 500 μm and production of parts with high surface finish have a lot of applications in industries[1]. Machining of materials on micro and sub-micro scale is considered a key technology for miniaturizing mechanical parts and complete machines. Micro-machining refers to small amount of material removal that ranges from 1-999μm [2]. Titanium (Ti) and its alloys possess the best strength-to-weight ratio and corrosion resistance among metals. Ti and its alloys have much higher fracture toughness, better electrical conductivity and greater biocompatibility. Therefore, they are very attractive for MEMS and biomedical uses [3].Machinability of titanium and its alloys is generally considered to be poor because titanium is very chemically reactive and, therefore, has a tendency to weld to the cutting tool during conventional machining, thus leading to chipping and premature tool failure. [4]. Non-traditional machining methods such as Electric Discharge Machining (EDM) and Laser Beam Machining (LBM) has been applied to the machining of titanium and its alloys during recent times. With EDM process, one problem is that the debris in machining gap cannot be eliminated easily, and the machining status is unstable during the process. LBM can be applied for machining of titanium, but even this process has its own problems in forming pear shaped holes and tapering of holes, holes with straight profile are difficult to obtain [5]. Ultrasonic machining (USM), with a thinner zone affected by machining, is suitable for hard and brittle materials. However, the disadvantages of USM are lower MRR compared with other processes and serious tool wear that usually affects machining precision [6]. Electrochemical machining could be one of the alternative processes for machining of Titanium. [7]. However, electrochemical machining of titanium is a challenge. Therefore, an attempt has been made in this paper to perform successful micromachining of titanium by generating blind micro holes with the help of EMM by the combination of various process parameters i.e. applied voltage, duty cycle, feed and frequency to evaluate their effect on machining of micro hole as well as overcut and surface roughness of the same. It is seen from the literature review that most of the literatures deal with conventional roughness studies and mostly using centre line average roughness (Ra) in ECM. However, a surface generated by machining is composed of a large number of length scales of superimposed roughness and generally characterized by three different types of parameters, viz., amplitude parameters, spacing parameters and hybrid parameters. [9]. Amplitude parameters are the ISSN: 2231-5381 http://www.ijettjournal.org Page 175

measures of the vertical characteristics of the surface deviations and examples of such parameters are centre line average roughness, root mean square roughness, skewness, kurtosis, peak-to-valley height etc. Spacing parameters are the measures of the horizontal characteristics of the surface deviations and examples of such parameters are mean line peak spacing, high spot count, peak count etc. On the other hand, hybrid parameters are a combination of both the vertical and horizontal characteristics of surface deviations and example of such parameters are root mean square slope of profile, root mean square wavelength, core roughness depth, reduced peak height, valley depth, peak area, valley area etc. Thus consideration of only one parameter like centre line average roughness is not sufficient to describe the surface quality though it is the most commonly used roughness parameter. In the present days many authors aims at consideration of five different roughness parameters, viz., centre line average roughness (Ra), root mean square roughness (Rq), skewness (Rsk), kurtosis (Rku) and mean line peak spacing (Rsm) for the surface texture generated in ECMM.[10]. The present study deals with the application of Taguchi method coupled with simulated annealing to determine the suitable machining process parameters in order to obtain optimum overcut and surface roughness characteristics in ECM process. An orthogonal array (L 16 ) is generated using the Taguchi design to carry out the experiments on Ti6Al4V. The machining parameters, viz., applied voltage (V), duty cycle (%), feed rate (µm/s) and frequency (Hz) are considered as independent variables. Analysis of variance (ANOVA) is also carried out to observe the level of significance of factors. A verification test is carried out in order to check the accuracy of the analysis. II. PROCESS PARAMETERS In this section the process parameters and the material under study are discussed. During ECMM, metal from the anode is removed atom by atom known as anodic dissolution. The ionized atoms of work piece material are then positively charged and are attracted away from the work piece by an electric field. The shape of the work piece due to anodic dissolution will be that of mirror image of the cathodic tool. In ECMM the material removal is governed by Faradays laws of electrolysis [11]. The factors that affect the rate of machining are the type of electrolyte, flow rate of electrolyte, temperature of electrolyte, and its ph [12]. The geometry, condition, and accuracy of the machined surfaces are depending on the electrolyte salt type and concentration, machining gap, pulse power supply setting, flow velocity and flow profile [13]. A. Electrolyte The electrolyte in the ECMM assists the dissolution of work piece material, carries electricity between the electrodes, carries away the removed material and heat generated, and maintains constant temperature in the machining area. The most commonly used electrolytes are Sodium Chloride and Sodium Nitrate. By using an electrolyte with a lower concentration, inter electrode gap could be reduced resulting in improved accuracy [14].For Titanium alloys in electrolysis with aqueous salt solutions produce titanium hydroxide with causes the electrolyte thick yellow colour after machining. Figure-1: Electrolyte before and after maching B. Pulsed current The amount of material removed is proportional to the quantity of current passed. Instead of continuous current, the use of pulsed current in ECMM facilitates prompt removal of hydroxides formed between electrodes and maintenance of IEG for better overcut and surface finish. The use of pulsed current gives good control over the machining process [16]. It is observed that the overcut is increased for increased pulse ON time indicating that the MRR is higher at lower frequencies. C. Voltage As machining voltage is increased, the machining rate is increased. The machining rate reaches its maximum at a particular voltage and decreased because electrode surface is gradually covered by bubbles generated at increased voltage [1]. It is observed that a power supply which maintains a constant voltage and current throughout the machining process is the most effective for electrochemical machining [15]. D. Duty cycle and frequency In a pulsed current, duty cycle is the ratio between power ON time and the total ON and OFF time i.e., The number of duty cycles used per unit time is called frequency (frequency =1/T total ). The duty cycle and frequency of the pulsed power supply affect the SR. [11]. During the experiments, pulse rectifier is switched on and the desired of ISSN: 2231-5381 http://www.ijettjournal.org Page 176

machining voltage, current, duty cycle and frequency are set before commencing the machining. E. Feed rate In ECMM process the inter electrode gap between tool and workpiece is maintained as small as possible (10 to 20 µm), the electrical resistance between tool and workpiece is least and the current is maximum and accordingly maximum metal is removed. The tool is feed into the work depending upon the how fast the metal is to be removed. When micro tool federate is very low then the machining time will increase causes more time available for tool to make hole, hence amount of EXPERIMENTAL PROCEDURE A. EXPERIMENTAL SETUP The experimental set up consists of various subcomponents e.g. mechanical machining unit, electrical power and controlling system, monitoring and measuring system etc. The mechanical machining system consists of CNC stage of 0.1μm resolution for all the three axes viz. X, Y and Z. The electrical power and controlling unit consists of DC pulsed power supply of capacity 20V with facility of variable duty ratio and frequency range of 1Hz to 200KHz were used for generating required nature of pulse power for micro machining operation. The nature and parameters of pulse has been monitored and measured with the help of digital storage oscilloscope (Synergy nano systems TTECM-10, India), and current s were measured with the help of digital multimeter. The micro hole inspection were performed with the help of vision measuring system (VMS-10) with a least count of 0.5 μm through the lenses of 10X to 50X optical magnification. The electrochemical micromachining experimental set up utilized in this present study is as shown in figure-1. Figure-2.Experimental set up B. EXPERIMENTAL DESIGN Taguchi technique is used to design and analyze the experiments. Based on the required quality objective, various parameters such as applied voltage, duty cycle, federate and frequency factors are selected. The various levels of parameter factors are determined which are on tool material, work material and size of hole. The factors and their levels are given in Table-1. Based on the levels used, the total degrees of freedom are calculated and suitable orthogonal array is chosen [10]. The experiments are carried out based on the orthogonal array. Experimental results are obtained and the ANOVA is carried to identify the contribution of individual parameters on Overcut and surface roughness. Blind hole is produced for convenience in measurement of surface finish using non contactable surface finish tester. Table-1: Factors and their levels. Factor Level-1 Level- Level- Level- 2 3 4 A 12 14 16 18 B 20 40 60 80 C 0.3 0.6 0.9 1.2 D 30 40 50 60 A. Applied voltage (V), B. Duty Cycle (%), C. Feed rate (µm/s), D. Frequency (Hz). C. EXPERIMENTATION In this study, the work piece specimen is made of 100 mm 60 mm 0.8 mm Ti6Al4V plate. The tool electrode is made up of tungsten of diameter 500μm. The electrolyte used for experimentation is fresh aqueous solution of sodium chloride having 20g/lit concentration. Variable rectangular DC pulsed supply has been used for experimentation. Applied machining voltages of 12, 14, 16 and 18 V have been selected for experiments. Duty cycle of 20, 40, 60 and 80% is applied for experiments. Feed rate of 0.3, 0.6, 0.9 and 1.2 are used and Frequencies of pulsed power supply of 30, 40, 50 and 60 Hz have been considered for various experiments. During the experiments, pulse rectifier was switched on and the desired of voltage, duty cycle and frequency is set before machining is commenced. The Taguchi method is used to determine various experimental combinations of parameters to be performed using L 16 orthogonal array. Experiments are performed by setting particular levels of parameters as per L 16 orthogonal array. The interactions between the machining parameters are neglected. The experimental combinations of machining parameters are as given below in the Table-2. The overcut (OC) is measured by measuring hole diameter using vision measuring machine by considering four points on perimeter of hole. Surface roughness is measured with non contactable surface roughness machine. The s calculated from the above machines are tabulated in Table-2. ANOVA is performed to determine dominant factor ISSN: 2231-5381 http://www.ijettjournal.org Page 177

significantly and it affects the OC and SR (Table-3). Using Minitab 17 software main effect plots are obtained. Regression equations are also formed to determine the optimum parameters for output parameters. Table-2: machining responses. Expt. No A B C D OC (mm) A. Applied voltage (v), B. Duty cycle (%), C. Feed rate (µm/s), D. Frequency (Hz) IV. RESULTS AND DISCUSSIONS SR (µm) 1 12 20 0.3 30 0.286 0.820 2 12 40 0.6 40 0.201 0.142 3 12 60 0.9 50 0.214 0.615 4 12 80 1.2 60 0.256 0.789 5 14 20 0.6 50 0.190 0.230 6 14 40 0.3 60 0.346 0.208 7 14 60 1.2 30 0.156 0.882 8 14 80 0.9 40 0.230 0.775 9 16 20 0.9 60 0.225 0.176 10 16 40 1.2 50 0.253 0.834 11 16 60 0.3 40 0.366 0.143 12 16 80 0.6 30 0.298 0.461 13 18 20 1.2 40 0.432 0.215 14 18 40 0.9 30 0.295 0.155 15 18 60 0.6 60 0.390 0.198 16 18 80 0.3 50 0.477 1.260 From the results obtained, the main effect plots are plotted between input and output parameters to get the individual effect of each input parameter on output. From the graphs overcut is mainly affected with applied voltage and feed rate. And surface roughness is affected with duty cycle. Figure-3:Main effect plots for overcut Figure-4: Main effect plots for surface roughness A. RESULTS OF ANOVA: Analysis of Variance (ANOVA) was executed on experimental data to find significance of the machining parameters towards the Percentage Improvement in Overcut and Surface Roughness. The pooled ANOVA of raw data for percentage improvement in R a are given in Table-3. ANOVA is evaluated to investigate the effects of each machining parameter on the observed s and to clarify which machining parameters significantly affect the observed s. In addition, the F test, named after Fisher, can also be used to determine which process parameters have a significant effect on the performance characteristic. Based on the table-3&4, it has been clear that the most significant parameter which affects the overcut is applied voltage and surface roughness is duty cycle. The F- of machining voltage in table-3 and duty cycle in table-4 are large, hence its percentage of contribution is also more. Table-3: ANOVA for overcut. F- valu e source DF Adj.SS Adj. MS P- % influenc e A 3 0.695 0.231 9.62 0.048 60.35 B 3 0.039 0.013 0.54 0.686 3.39 C 3 0.359 0.119 4.97 0.110 31.18 D 3 0.058 0.019 0.81 0.566 5.08 Error 3 0.072 0.024 Total 15 1.223 Table-4: ANOVA for surface roughness. source DF Adj.SS Adj. MS F- P- % influen ce A 3 0.064 0.021 0.24 0.863 4.98 B 3 0.485 0.162 1.84 0.315 38.18 C 3 0.344 0.114 1.30 0.417 26.97 D 3 0.380 0.127 1.44 0.386 29.87 Error 3 0.234 0.088 Total 15 1.537 B. REGRESSION EQUATIONS: Four independent variables, such as applied voltage (V), duty cycle (DC), feed rate (f) and frequency (F) are observed; all the four are major factors, interaction and pure quadratic term in micro-ecm affects the quality of ISSN: 2231-5381 http://www.ijettjournal.org Page 178

titanium alloy. The second order polynomial to develop a mathematical model of the data equation is used to convey the overcut (OC) and surface roughness (SR) of ECMM process with four input factors. To develop a mathematical model of the data collected for overcut and surface roughness, the multiple regression analysis of the data of second order done using Minitab-17. The equations obtained are OC = -3.66 + 0.628* V + 0.00680 *DC + 2.041 *f- 0.0230 *F*- 0.02371 *V^2-0.000084 *DC^2-1.144 *f^2 + 0.000216 *F^2 SR = -1.40 + 0.227 * V + 0.0149*DC + 2.12 *f - 0.0238 *F- 0.0068* V^2-0.000216 *DC^2-1.490 *f^2 + 0.000293 *F^2 D. SURFACE ROUGHNESS PARAMETERS: Surface roughness is measured with non contactable surface roughness tester. For convenient in measurement blind hole is produced throughout the experiment, otherwise for through hole cutting operation is performed (Ti alloys are very hard materials so, WEDM or AWJM is used to cut the material at hole). Various surface parameters are easily find out with help of surface profile scanned by the machine. The following figure indicates two graphs which are represents roughness and waviness graphs for surface texture. And the diagrams represent 3-D view of the measured profile and advanced 3-D view with surface parameters. C. SIMULATED ANNEALING: The variation of functional s with respect to number of iterations is shown in figure-5. The same figure shows best point vs. Number of variables plot (V, DC, f and F has been assigned as number of variable 1, 2, 3 and 4 respectively). This means final optimal process parameters obtained from the result of SA and their respective regression equation s are shown in the table Table-5: Optimal result for OC obtained from SA Optimal machining parameters V = 18v, DC = 20.7%, f= 0.3µm/s, F= 43.6 Hz Predicted optimum from SA OC= 0.17735mm Experimental OC = 0.167mm Figure-6: Roughness and waviness graphs for surface profile Table-6: Optimal result for SR obtained from SA Optimal machining parameters Predicted optimum from SA Experimental V=12v, DC=61.02%, f = 1.2µm/s, F = 50.8Hz SR=0.24977µm SR=0.208µm Figure-5: Function vs. Iteration Figure-7: 3-D & advanced 3-D views for Surface profile (Ex no-4) ISSN: 2231-5381 http://www.ijettjournal.org Page 179

V. CONCLUSIONS In this work, the effect of applied voltage, duty cycle, feed rate and frequency of the ECMM process on overcut and surface roughness during machining of Ti6Al4V is studied. The process parameters such as electrolyte concentration and inter electrode gap successfully maintained at the desired s during all the experiments. Experimental study is successfully conducted on the developed ECMM system. Taguchi L18 orthogonal array is used for the experimentations. ANOVA is performed to analyze the experimental results. 1. The machining of micro holes in titanium based alloy (Ti6Al4V) through ECMM process is relatively different compared to commonly used metals especially in terms of applied machining voltage, it requires higher voltages. 2. Stray current effect is observed due to electrolyte characteristics and/or improper selection of inter electrode gap. 3. Based on ANOVA, the most significant parameters that influence the overcut is found to be machining voltage and surface roughness is found to be duty cycle. 4. The optimum parameters are obtained from Simulated Annealing gives good results in the minimization of overcut and surface roughness. [12] Bhattacharyya B., Doloi B. and P.S. Sridhar. 2001. Electrochemical micro machining: new possibilities for micro manufacturing. Journal of Material Processing Technology. 113: 301-305. [13] Bhattacharyya B., Mitra S. and Boro A. K. 2002. Electrochemical Micromachining: New possibilities for micromachining. Robotics and Computer integrated manufacturing. 18: 283-289. [14] Bhattacharyya B. and Munda J. 2003. Experimental investigation in to electrochemical micromachining (EMM) process. Journal of Materials Processing Technology. 140: 287-291. [15] Thanigaivelan R and Arunachalam R.M. 2010. Study of dominant variables in Electrochemical Micromachining. Manufacturing Technology Today. (1): 22-28. [16] Thanigaivelan R and Arunachalam R.M. 2010. Experimental study on the influence of tool electrode tip shape on Electrochemical Micromachining of 304 stainless steel. Materials and Manufacturing Processes. 1532-2475, 25(10): 1181-1185. REFERENCES [1] Rajurkar K. P., D. Zhu, J. A. McGeough, J. Kozac and A. De Silva. 1999. New Developments in Electrochemical Machining. CIRP Annals- Manufacturing Technology. 48(2): 567-579. [2] Bhattacharyya B., Malapati M. and Munda J. 2005. Experimental study on electrochemical micromachining. Journal of Materials Processing Technology. 169(3): 485-492. [3] L. M. Jiang, W. Li, A. Attia, Z. Y. Cheng, J.Tang, Z. Q. Tian, Z. W. Tian method for electrochemical micromachining of titanium alloy Ti6Al4V, (2008) 38:785 791 [4] Ezugwu E.O., Wang Z.M., Titanium alloys andtheir machinability-a review, Journal on Materials Processing Technology 68 (1997) 262-274 [5] Kumar Jatinder, Khamba J.S., Mohapatra S.K An investigation into the machining characteristics of titanium using ultrasonic machining,int. J. Machining and Machinability of Materials, Vol. 3, Nos. 1/2, 2008 [6] Yan Cherng Lin, BiingHwa Yan, Yong Song Chang, Machining characteristics of titanium alloy (Ti6Al4V) using a combination process of EDM with USM Journal of Materials Processing Technology 104 (2000) 171-177 [7] Madore C., Landolt D., Electrochemical micromachining of controlled topographies on titanium for biological applications J.Micromech. Microeng,7 (1997) 270-275 [8] Dhobe Shirish D., Doloi B., Bhattacharyya B Surface characteristics of ECMed titanium work samples for biomedical applications Int J Adv Manuf. Technol (2011) 55:177-188 [9] Sahoo, P., 2005. Engineering Tribology, Prentice Hall of India, New Delhi. [10] Milan Kumar Das, Kaushik Kumar, Tapan Kr. Barmana International Conference on Materials Processing and Characterisation ICMPC 2014 Procedia Materials Science 6 ( 2014 ) 729 740 [11] R. E. Sorace, V. S. Reinhardt, and S. A. Vaughn, Highspeed digital-to-rf converter, U.S. Patent 5 668 842, Sept. 16, 1997. ISSN: 2231-5381 http://www.ijettjournal.org Page 180