Modeling and Analysis of Micro-WEDM Process on Inconel Super Alloy through Response Surface Methodology

Transcription

1 Modeling and Analysis of Micro-WEDM Process on Inconel Super Alloy through Response Surface Methodology Sivaprakasam.P 1*, Hariharan.P 2, Gowri.S 3 1* Anna University,Chennai, , India, shiva_au@rediffmail.com. 2 Anna University, Chennai, , India, hari@annauniv.edu. 3 Anna University, Chennai, , India,sgowri@annauniv.edu. Abstract This paper presents modeling and analysis of machiningcharacteristics of microwire electro discharge machining (micro-wedm) process on inconel alloy 718 using the response surface methodology (RSM). The input variables of micro-wedm process are voltage, capacitance and feed rate. The material removal rate is considered as a response variables. Experiments were carried out on inconel alloy 718using central composite design (CCD). The RSM models have been developed based on experimental designs. Analysis of variance (ANOVA) has been employed to test the significance of RSM model. It has been found out that all the three process parameters are significant and their interaction effects are also significant on the MRR. Finally predicted values were compared with experimental values. Key Words: Micro-WEDM, ANOVA, Inconel alloy 1. Introduction Micro-WEDM is recognized as an effective machining technique used in a wide range of applications namely automotive industry, aerospace, defense, electronics, telecommunications, healthcare, environmental, industrial products, and consumer products of micro feature with microscale dimension and nano level surface finish. Micro-EDM is similar to macro EDM process, material is eroded by series of electrical discharge between the work piece and a wire electrode immersed in a liquid dielectric medium. These electrical discharges melt and vaporize very small amounts of the work material, which are then ejected and flushed away by the dielectric. There is no contact between tool and work piece, any conductive material can be machined by WEDM regardless of their hardness and toughness. Most of the materials used in these industries are either super alloys or some other difficult to machine materials like ceramics, glass and silicon wafers. Manufacturing processes such as micro moulds, micro holes etc on these materials would be almost impossible owing to high tool wear rate and expenses involved. Hence certain nontraditionalmicromachining techniques are involved in order to meet the present demand for high accuracy. The earlier studies on machinability of inconel 718 were mainly on EDM, WEDM operations. (Aspinwalletal., (2008), Newton et al., (2009), Hewidy et al.(2005), Prabhuet al.,(2011), Thomaset al.,(2009),bozdana et al., (2009), Anil Kumar et al., (2011),Pushpendra and Bharti (2010)). Nickel based super alloys are extensively used in high temperature applications such as gas turbines, electric power generation equipment, nuclear reactors and high temperature chemical vessels. Inconel 718 is a high strength, temperature resistant (HSTR) nickel-based super alloy. It is extensively used in aerospace applications, such as gas turbines, rocket motors, and spacecraft as well as in nuclear reactors, pumps and tooling.(kuppan et al., 2008).Only few published information is available on micro-edm /WEDM studies of inconel 718.So there is a scope for investigating the micro machining process to develop mathematical models to enhance the process performance. The present study describe that central composite design is used to develop mathematical models for output response and to analyze the effects of 443-1

2 Modeling and Analysis of Micro-WEDM Process on Inconel Super Alloy through Response Surface Methodology process parameters of micro-wedm process using inconel alloy Response Surface Methodology (RSM) RSM is a collection of statistical and mathematical techniques useful for design of experiments and optimizing process parameters RSM used for determining and representing the cause and effect relationship between the responses and input control variables influencing the responses as a two-or three-dimensional hyper surface.(krishnaiah, K and Shahabudeen, P. 2012). Lin et al.,(2012) evaluated the machining characteristic of micro-edm using response surface methodology. RSM based on the CCD could efficiently be applied for the modeling of micro- WEDM. 3. Experimental methods and Materials The experimental work was conducted using micro WEDM (DT110, Mikrotools Inc., (Singapore) setup with an RC Circuit positional accuracy of 0.1 micrometer shown in Fig 1. A cylindrical zinc coated copper wire was used as the tool electrode materials with a diameter of 70µm and work piece material was a thin metal plate of inconel alloy 718 thickness of 1mm, length 5mm and width 10mm. Commercial grade EDM oil was used as dielectric fluid. The different input factors and their level of micro-wedm process are depicted in Table 1. Material removal rate was calculated using Eq. (1). Table 1 Input Factors and their levels Variable Symbol Levels Voltage (V) A Capacitance (µf) B Feed Rate (µm/s ) C Figure 1 Experimental Set-up for Micro-WEDM 4. Results and Discussion Machining of inconel alloy with different machining condition using and the results are discussed in the following section. Twenty different experimental combinations were chosen at random according to CCD in RSM. The experimental study was carried out based on CCD given in Table 2. The experimental results of machining performance of micro-wedm process are presented in Table 2. Table 2 Experimental results for MRR Run A B C Voltage (V) Capacitance (µf) Feed Rate (µm/s MRR (mm 3 /min)

3 4.1Analysis of Material Removal Rate The main effects and interaction effects of various process parameters on MRR are presented in Table 3. It is found that the discharge voltage (A), capacitance(b), feed rate (C) interaction term voltage and capacitance (AB), pure quadratic effect of voltage (A 2 ), capacitance (B 2 ) and feed rate (C 2 ) have significant effect on MRR. Figure 2 shows the three dimensional (3D) response surface of MRR, varying discharge voltage and capacitance. Figure 2 shows the tendency of MRR increase due to increase in voltage and spark energy across electrode gap and also MRR tends to increase with the increase in capacitance. During micro-wedm process the materials melt and vaporization occurs while temperature rises in the work piece materials. The material removal rate is influenced by a discharge energy which is based on nature of electrical and thermal conductivity of the work piece materials. Table 3 Analysis of variance for MRR Source SS D OF Mean Square F Valu e p-value Prob > F Model < A < B C AB A B C Residu al Lack of Fit Pure Error Cor Total SS=Sum of Square DOF = Degree of freedom Figure 3 Contour plot of MRR It has been found that the MRR gradually increases when the increase of voltage and capacitance. Similarly it tends to incenses when feed rate is increased.similarly it tends to incenses when feed rate is increased. MRR decreases due to high gap pollution and insufficient flushing conditions at high levels of voltage and capacitance. The higher value of MRR mm 3 /min is achieved with voltage = 100 V, capacitance = 0.4µF and feed rate = 15µm/s within the experimental range. The contour plot of A and B for predicting the MRR is depicted in Figure 3 The statistical analysis (ANOVA) indicates that quadratic model of MRR is statistically significant and lack of fit not significant. Insignificant factors are eliminated by backward elimination process and the reduced model is shown in ANOVA Table 3. (R 2, adjusted R 2 values of the model are 96.69% and 94.76%, respectively). 4.2 Mathematical Modeling The adequacy of model can be decided by normality and independence based onresidual analysis. The residual plot for the response parameter material removal rate is shown in Fig. 4. From the Fig. 4 it can be inferred that the residuals are spread approximately in a straight line, which shows good correlation between experimental and predicted values and the variable follows the normal distribution. From the Fig. 4 it can be inferred that the errors are normally distributed. Figure 2 3D Surface plot of MRR Fig. 4 Normal probability plot 443-3

4 Modeling and Analysis of Micro-WEDM Process on Inconel Super Alloy through Response Surface Methodology Fig. 5 Residuals versus Predicted values Figure7 Experimental and predicted results of MRR From the developed model Eqn.(2) for MRR shows that, all the three main factors and interaction of voltage and capacitance having more influencing on MRR. Plot of the predicted and experimental results is shown in Figure 4. Fig. 6 Residual versus Order of Experimentation From Figures 5&6 it can be inferred that the residuals are randomly scattered indicating that they are independent. Three independent variables are considered, such as voltage (A), capacitance (B) and feed rate (C); all the three are major factors in micro-wedm affecting the qualities of inconel alloy. The secondorder polynomial equation is used to convey the Material removal rate with machining parameters for the micro-wedm, namely voltage (A), capacitance (B), feed rate (C). The regression coefficients of the second order equation are obtained by using the experimental data. The regression equation for the material removal rate as a function of three input process variables was developed using experimental data and is given below. Some of the insignificant terms are eliminated in the quadratic model equation. Model equation of MRR Y A B A B A B C 2 4.3Single objective Optimization Single response optimization was carried out using desirability function in conjunction with response surface methodology. The goal is to maximize the material removal rate. Desirability approach helps us to map between the predicted response y and desirabilityfunction d. The desirability value varies from 0 to 1. If the desirability value is zero it indicatesthat predicted value is completely undesirable and the desirability value of one is the idle.thedesirability of corresponding response increases as the value of d increases. The final step is validating the model through the use of optimal machining parameter using confirmation test. Confirmation experiments were conducted at optimum machining conditions shown in Table 4. The optimized values of material removal rate are mm 3 /min using the confirmation experiments. The confirmation experiment results were found within 95% confidence interval. Table 4 Optimum machining conditions Goal Maximum Desirability MRR MRR Optimal combination Actual predicted Voltage (V) A 100 Capacitance B 0.4 (µf) Feed Rate (µm/s ) C

5 5 Conclusions This research work is presented single objective optimization process parameters of micro- WEDM of Inconel alloy using response surface methodology.the statistical analysis (ANOVA) highlighted that the major influencing machining parameter considered in this study improves machining performance of micro-wedmprocess. The mathematical modeling was presented for predicting optimal condition of material removal rate and statistically validated by ANOVA.The three machining parameters voltage, capacitance, feed rate, interactions term of voltage and capacitance (AB), and pure quadratic effect voltage (A 2 ), capacitance (B 2 ) and feed rate (C 2 ) have significant influence on material removal rate of micro-wedmprocess on inconel alloy. The optimal machining performance inconel alloy cloud be achieved is at voltage of 100V, capacitance of 0.4µF and feed rate of 15µm/sec. This parameter combination produce higher material removal rate equal to mm 3 /min could be achieved. Finally predicted values and experimental values were compared and error percentage is 3.36%. References [1] Aspinwall, D.K., Soo, S.L., Berrisford,A.E. and Walder. G. (2008), Workpiece surface roughness and integrity after WEDM of Ti 6Al 4V and Inconel 718 using minimum damage generator technology,cirp Annals - Manufacturing Technology, [2] Newton, T.R., Melkote, S. N., Watkins, T.R., Trejo, R. M., and Reister, L. (2009). Investigation of the effect of process parameters on the formation and characteristics of recast layer in wire-edm of Inconel 718. Materials Science and Engineering: A, 513, [3] Hewidy,M.S., El-Taweel,T.A. and El-SaftyM.F. (2005), Modelling the machining parameters of wire electrical discharge machining of Inconel 601 using RSM, Journal of Materials Processing Technology, 169, [4] Prabhu, S.and Vinayagam, B.K. (2011), AFM surface investigation of Inconel 825 with multi wall carbon nano tube in electrical discharge machining process using Taguchi analysis, Archives of Civil and Mechanical Engineering, Vol. XI, [5]Thomas R. Newton, Shreyes N. Melkote, Thomas R.Watkins, Rosa M. Trejo and Laura Reister(2009), Investigation of the effect of process parameters on the formation and characteristics of recast layer in wire- EDM of Inconel 718, Materials Science and Engineering A , [6] Bozdana, A.T., Yilmaz, O.,OkkaM.A.and Filiz İ.H. (2009), 5th International Conference and Exhibition on Design and Production of MACHINES and DIES/MOLDS, JUNE TURKEY. [7] Anil Kumar, Sachin Maheshwari, Chitra Sharma, and Naveen Beri, (2011),Analysis of Machining Characteristics in Additive Mixed Electric Discharge Machining of Nickel-Based Super Alloy Inconel 718, Materials and Manufacturing Processes, 26: [8] Pushpendra and S.Bharti (2010), Experimental investigation of inconel 718 during die-sinking Electric discharge machining,international Journal of Engineering Science and Technology,Vol. 2(11), [9]Kuppan, P., Rajadurai, A.and Narayanan, S. (2008), Influence of EDM process parameters in deep hole drilling of Inconel 718, Int J Adv Manuf Technol 38: [10] Krishnaiah, K and Shahabudeen, P. (2012) Applied Design of Experiments and Taguchi Methods, PHI Learning Private Limited New Delhi [11]Lin, Y. C., Tsao, C. C., Hsu, C. Y., Hung, S. K., and Wen, D. C. (2012). Evaluation of the characteristics of the micro-edm process using response surface methodology based on the central composite design. Int J Adv Manuf Technol 62(9-12),