Dataset on optimization of EDM machining parameters by using central composite design

Newly prepared titanium alloy (Ti-13Zr-13Nb (TZN)) using powder metallurgy is considered in this investigation. Titanium alloys (TZN) are used in hip and knee replacement for orthopedic implants. Conventional machining, TZN alloys produce higher tool wear rate and poor surface quality, but this can be reduced by Electrical Discharge Machining (EDM) method. Moreover, EDM produce good biological and corrosion resistant surface. In this research, experiments were conducted by considering the influential process factors such as pulse on time, pulse off time, voltage, and current. The experiments were designed based on Response Surface Methodology (RSM) of face centered central composite design. Analysis of Variance (ANOVA) was conducted to identify the significance process factors and their relation to output responses such as Electrode Wear Rate (EWR), Surface Roughness (SR) and Material Removal Rate (MRR). Further, an empirical model was developed by RSM in order to predict the output responses.


Subject area
Materials science More specific subject area Bio materials Type of data Text file, tables, graphs and figures How data was acquired Experimental investigation Data format Raw, calculated, analyzed, tabulated, contour plotted Experimental factors Input factors (pulse on time, current, pulse off time and voltage) and output responses are electrode wear rate, material removal rate and surface roughness.

Experimental features
In this prepared alloy specimens were machined by using electrical discharge machine with different operating conditions. Data source location School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India Data accessibility Data is with the article. Related research article Sengottuvel, P., S. Satishkumar, and D. Dinakaran. Optimization of multiple characteristics of EDM parameters based on desirability approach and fuzzy modeling. Procedia Engineering, 2013 [12]. https://doi.org/10.1016/j.proeng.2013.09.185

Value of data
This data set has innovative information on EDM machining parameters for orthopedic implant applications.
Data would be valuable to the researcher those who are doing research on optimization of EDM parameters for machining titanium alloy (TZN).
To understand the empirical relationship between EDM input factors and output responses.

Data
The date presented information on alloy preparation, EDM machining parameter, material removal rate, electrode wear rate, surface roughness and optimum EDM machining parameter. Table 1 shows the characteristics of the powders used in the Ti-13Nb-13Zr alloy preparation. Chemical composition of the powders used in this experiment in Table 2. Tables 3-5 show the EDM operating conditions, Levels of EDM Machining Parameters and Experimental designs data. ANOVA for Material Removal Rate, Electrode Wear Rate and Surface Roughness are presented in Tables 6-8. Table 9 shows the optimum parameters for EDM machining parameters, while Table 10 represents predicted and observed values of TZN alloy.

Materials
The materials used in the investigations are titanium, niobium and zirconium powders. The characteristics of these powders are shown in Table 1.

Methods
The step by step processes selected for production of alloy materials (Ti-13Zr-13Nb) are Blended Elemental Method (BE), cold uni-axial pressing, cold isostatic pressing and vacuum sintering.
Hydride-dehydrate process (HDH) is adapted to make the elemental titanium powders. In the hydride process, titanium powder is produced in the vertical furnace (at 500°C and for 3 h) with positive pressure [1]. Subsequently at ideal temperature of a room, the hydride was granulated in a niobium container under vacuum of 10 À 2 Torr. In continuation, niobium and zirconium powders are produced in the similar process with the temperature range of 800°C. The powder production is carried out using hydride process to produce increased sintering rate and reduced cost. The chemical compositions of the powders are tabulated in the Table 2 [2].
Initially, the powders are weighed in lot about 4 g and mixed at time interval of fifteen minutes using a double-cone blender. After mixing of powders, cold uniaxial pressing process is performed on   the powders at 60 MPa in cylindrical (15 mm diameter) steel die without lubricants. Subsequently, cold isostatic press is used to pressurize the specimen at 350 MPa for duration of 30 s. The specimens are encapsulated under vacuum of 10 À 2 Torr in flexible rubber molds. Thermal Technology equipment was adapted to conduct the sintering process in niobium container with vacuum of 10 À 7 Torr and sintering temperatures were kept around 900-1500°C with heating rate of 20°C/min. Later arriving at the low temperature, specimens were kept at the selected temperature for an hour and subsequent to that, furnace is cooled to room temperature. Tradition methods were utilized to prepare the metallographic specimens [3]. The work materials (TNZ alloys) were used with the dimensions of 20 mm diameter and length of 35 mm and diameter of 10 mm graphite electrode (for higher MRR and lower EWR) was applied in the  Table 3. The impulse jet flushing system using commercial grade kerosene (the dielectric fluid) was utilized to blush off the foreign contaminants from the igniting region in the EDM [4]. All the specimens are machined using EDM within 20 min. The electrode wear rate and material removal rate is computed by using the weight variation of the work piece and electrode material earlier and later the machining by digital weighing scale (0.001 g precision

Experimental design
The experiment is designed based on face centered central composite design by using response surface methodology [6].

Parameters and levels
EDM operating parameters such as voltage, current, pulse on time and pulse off time have a prominent effect on the machining performance of titanium alloys [7]. Each parameter was placed at three equally spaced values generally coded as level À 1 (minimum value), level 0 (central value), and level þ1 (maximum value). The range of the input parameters pulse on time, current, pulse off time and voltage were selected as 6-10 ms, 8-16 A, 7-11 ms and 50-70 V respectively as shows Table 4.

Design of experiments
RSM is an effective tool for developing, improving, and optimizing the processes by combining several input variables and assessing how their complex interactions affect the performance of the response variables [2,5]. In this study the numbers of trials were designed by using Response Surface Methodology (RSM). The input portion of the Central Composite Design is a full factorial design with all the sequence of the parameters at three stage (high þ 1 and low À 1) and collected of eight star points and six central points (coded level 0) [1]. The Central Composite Designs contains thirty experimental values at four input factors and after conducting experiments the output responses are shown in Table 5 [8].

Statistical analysis
Analysis of variance (ANOVA) was conducted with the aim of evaluating the influence of pulse on time, current, pulse off time and voltage. Tables 6-8 shows the results of ANOVA for material removal rate, electrode wear rate and surface roughness. The analysis was carried out at 5% significance level and 95% confidence level [4].

Mathematical model for MRR, EWR and SR
The empirical models developed for output response material removal rate, electrode wear rate and surface roughness were evaluated by the F test. From the results the mathematical model is statistically valid to evaluate the output variable. The adequacy of model is tested using ANOVA analysis. It was found that the model F-ratio of 720.076 was obtained for material removal rate. However, the F-ratio of the lack of fit is 1.0253. It was found that the model F-ratio for electrode wear rate is 3.415 and the F-ratio of the lack of fit is 0.021. it was found that the model F-ratio for surface roughness is 5.1383 and the F-ratio of the lack of fit is 0.544. Hence the models are notable and their lack of fit is inconsiderable.

Effect of process parameters on material removal rate (MRR)
When the pulse current and voltage`applied to the EDM machine was lesser, it reduces the output discharge energy. So lesser discharge energy will be applied into the machining zone, it causes poor material removal rate, fabricated chamber was narrower and the debris was easily evacuated from machined region. In reverse increase the voltage and current it produces higher the value of discharge energy.so wider chamber developed in the work specimen and also it distracts the electrical discharge, so it creates short circuit in EDM, results in small material removal rate. Hence optimum rate of current and voltage is essential to produce higher MRR. Fig. 1 displays the 3D surface plot for material removal rate in connection to the input factors such as current, pulse on time, voltage and pulse off time [1]. Fig. 1(a) displays the impact of current and voltage on material removal rate. When the voltage and current increases, It can be seen that the MRR increases significantly. When the pulse off time and voltage increases, considerably the MRR is also increased shown in Fig. 1(b). Fig. 1(c) and (d) shows the impact of pulse on time and current, pulse on time and voltage on MRR. It can be observed that the pulse on time increases, the MRR value is also increased. Fig. 1(e) display the impact of pulse off time and current on MRR. Fig. 1(f) depict the impact of pulse off and pulse on time on MRR. Thus the voltage, pulse on time, current and pulse off time are important parameters for material removal rate [7].

Effect of process parameters on electrode wear rate (EWR)
The electrode wear rate is a changing case which is altered by voltage, pulse on time, current and pulse off time with different input values. In EDM, the eroded materials from both work piece and tool, the damaged carbon particles from dielectric fluid may be accumulated on the tool face.it act as a protective layer in tool surface, that will help to reduce the tool wear rate.it can be achieved by higher value of pulse duration, lower value of pulse off time and pulse current. Fig. 2 shows the relationship between input factors and electrode tool wear rate. Fig. 2(a) display the effect of voltage and current on EWR. When the pulse current increases, the value of EWR also increases. But either increases or decreases the value of voltage does not affect the value of EWR [9]. The same to be noted on Fig. 2(b) and (f). it means that voltage is inconsiderable factor for electrode wear rate. Whereas pulse on time, pulse off time and current is notable factors for electrode tool wear rate, it can be displayed in Fig. 2(c)-(e).

Effect of process parameters on surface roughness (SR)
The high electrical discharge between tool and work piece produces crater wear on work piece surface which introduces poor surface finish.so optimum parameters to be needed to control the surface roughness. Fig. 3 shows the relationship between input variables (pulse on time, current pulse off time and voltage) and response (surface roughness).when the value of pulse on time and current rising simultaneously the surface roughness value also increases, it can be shown in Fig. 3 Fig. 2(b) and (d), the roughness value is decreased up to 60 V and further rising the input voltage the value increases. Thus increasing or decreasing the value of pulse off time does not affect the surface roughness.so pulse off time is insignificant parameters for surface roughness [10].

Optimization and validation
The sequence has been valuated with the aid of Design Expert software version7.0. The desirability falls between zero and one. The solution with the highest desirability and close to one is chosen as the optimal setting and the validation experiments are conducted. The optimal parameters setting and the corresponding output values as shown in Tables 9 and 10.Through confirmatory experiments, it is observed that the absolute error between predictions and actual values fall within 10% [4,11]. Thus the model can be effectively used to predict the EDM machining parameters.

Transparency document. Supplementary material
Transparency data associated with this article can be found in the online version at https://doi.org/ 10.1016/j.dib.2019.01.019.