Influence on machinability and form tolerance of Inconel 718 in Edm using different diameter multi hole Cu electrodes
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Abstract
This research aims to examine the machinability and form tolerances in die sinking EDM for Nibased superalloy with different diameter internally engraved hole of the multihole copper electrode. Manufacturing of superalloys with close tolerances is becoming a major area for primary research in defence and aerospace industries due to their particular characteristics. Therefore, this work focuses on an experimental analysis to improve the productivity and Material Removal Rate of Inconel718 with close tolerances. The most dominating process constraints, viz. hole diameter of Multihole electrode (D), Peak current (I_{p}), Pulse on Time (T_{on}) and dielectric fluid pressure were selected as process constraints to conduct experimental trials. The Material Removal Rate, EWR and form tolerances were considered as output responses. The experimental outcomes were optimized by Taguchi analysis and multiparametric optimization method GRA. A Fuzzy logic model using Matlab was developed for the prediction of performance parameters, namely MRR, EWR, circularity and cylindricity with respect to changes in input parameters. Three MF’s (‘Trimftriangular membership functions’) were allocated to each input response, whereas five MF’s were allocated to output responses. The Fuzzy model shows the 94.01% accuracy between the experimental values and the predicted values. From the results, it is concluded that the use of a multihole electrode leads to a higher rate of MRR. Moreover, the form tolerance deviation improves with the increment of T_{on} value. The optimized parameters showed a considerable improvement in the process and will facilitate the aerospace and defence industries to improve the productivity of Inconel718 with close tolerance.
Keywords
Electric discharge machining (EDM) Fuzzy logic system MRR EWR Form tolerance Taguchi Grey relational analysis (GRA)1 Introduction
Highly precise products with close tolerances are manufactured by nonconventional machining methods in aerospace and defence industries. Specifically, electric discharge machining (EDM) is practically versatile applications of nonconventional machining in precision manufacturing industries to manufacture precise and close tolerance parts with higher accuracy. Therefore, it is the requirement that regular estimations should be made to measure the form tolerances [1, 2, 3, 4, 5].
Nickelbased superalloys are extensively used in high precision components because of its excellent properties [11, 12, 13]. However, based on the properties Inconel 625 is a well identified difficulttomachine superalloy [14]. Inconel 625 wrought superalloy has a high cutting temperature due to its lesser thermal conductivity and specific heat. Furthermore, builtup edge (BUE) engrave at the tip of the tool, when this superalloy is machined by using traditional machining processes. Therefore, EDM has been explored for the machining of this superalloy by using copper and brass electrodes [15).
Various researchers have been reported work on EDM to measure the influence of input parameters on performance parameters. As an attempt to use the EDM process effectively, researchers reported the dominance of EDM parameters in hole drilling of nickelbased superalloy [16].
Narender Singh presented multiple performance characteristics optimizations for EDM constraints by applying the Taguchi based Grey relational Analysis method (GRA) for AL10% SiC composites. Li demonstrated the application of greyfuzzy logic based orthogonal array (OA) for optimization [15].
Form Tolerance may be described as the deviation between the maximal and minimal limits and the total measure that a particular dimension is allowed to deviate. Tolerances are specified generally by two methods; unilateral tolerance and the bilateral tolerance. Unilateral tolerance allows the variance for a nominal measure in one direction only, whereas the bilateral tolerance allows the dimensional variation in both the directions from the specified value [2, 17, 18].
Stanislaw [8] investigated the importance of cylindricity measurement by using the reference method. Adamczak presented the principle of reference method and also presented the method for comparing the cylindrical profile [22, 23] measured and analyzed the cylindricity, diameter, roundness, straightness and taper for EDM microholes by using coordinate measuring machine (CMM). Therefore, the importance of form tolerance in manufacture components was discussed.
Volkan Yilmaz and Murat Sarikaya et al. [24, 25, 26] optimized the EDM performance parameters namely machining rate, WR (wear rate), AOC (average overcut) and taper angle by using Taguchi, RSM, Regression analysis and ANNs (artificial neural networks) for µEDD (Electrical discharge drilling) of AISI304 SS and Hand field steel. The authors concluded that discharge current had the most significance on performance parameters. Guren Meral et al. [27] statistically optimized the Ra value, torque and thrust force for two drill geometries on AISI4140 using Taguchi based GRA method.
Some researchers have been reported the use of different shape Cu electrodes and multihole electrodes to predict the machinability in the EDM process [28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]. WlTaweel [28] concluded that the AlCuSiTiC powder sintered electrodes are more sensitive to T_{on} (pulse on time) and peak current. Khan [29] demonstrated the effect of Cu and brass electrodes to measure electrode wear and MRR (material removal rate) during EDM of Al and mild steel. The author concluded that the Cu electrode has a low wear rate and highest MRR as compared to the brass electrode. The wear rate increases with the increase in both voltage and current. Kin et al. [35] concluded that the machinability of Cu electrode is higher and the bigger DIA. Of multihole electrode reduces the MRR. Govindan and Murugesan et al. [36, 37] investigated and optimized the EDM parameters by GRA method using multihole electrodes.
From the literature survey, it is ascertained that no plausible works were reported to measure form tolerances such as cylindricity and circularity on an Inconel718 Nibased superalloy using a different diameter circular shape multihole copper electrode in EDM process. Therefore, this experimental analysis and multiobjective optimization work being undertaken to improve the form tolerances in EDM by Taguchi analysis, Fuzzy logic and GRA method.
2 Experimental setup
Allocated values of EDM constraints and their levels
Factor  Parameter  Units  Level1  Level2  Level3 

A  Electrode hole DIA. (d)  mm  0.08  0.16  0.24 
B  Peak current (I_{p})  Amp  4  8  12 
C  Pulse on time (T_{on})  µs  200  400  600 
D  Dielectric. fluid pressure  Kg/m^{2}  0.1  0.2  0.3 
The Inconel718 workpiece was used in the form of a 4 mm thick rectangular plate. The workpiece and the electrodes were linked up with +ve and –ve polarity in the D.C. power source, respectively. Dieelectric kerosene along with various pressure ranges was used with centre flushing technique for the experimental work. The weight of the electrodes and workpiece was measured before and after machining for every trial run with digital weightbalance (up to 0.001g accuracy).
Each trial was evaluated thrice and the mean values were obtained. The form tolerances namely cylindricity and circularity were measured by using a TESA MicroHite 3D coordinate measuring machine (CMM).
3 Form tolerance analysis
DOE matrix of L9 orthogonal array (OA)
Sr. nos.  Electrode hole DIA. (d)  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

1.  0.08  4  200  0.1 
2.  0.08  8  400  0.2 
3.  0.08  12  600  0.3 
4.  0.16  4  400  0.3 
5.  0.16  8  600  0.1 
6.  0.16  12  200  0.2 
7.  0.24  4  600  0.2 
8.  0.24  8  200  0.3 
9.  0.24  12  400  0.1 
Measured values for output responses using circular profile multihole Cu electrode, as per DOE
S. nos.  MRR (g/min.)  EWR (g/min.)  Circularity (mm)  Cylindricity (mm) 

1.  0.003  0.0009  0.0337  0.0441 
2.  0.067  0.00016  0.0112  0.0135 
3.  0.082  0.00016  0.0536  0.0633 
4.  0.045  0  0.0710  0.0913 
5.  0.062  0  0.0205  0.0093 
6.  0.094  0.0088  0.0557  0.0602 
7.  0.033  0  0.5584  0.0102 
8.  0.050  0  0.0791  0.0538 
9.  0.049  0  0.0100  0.0185 
3.1 Taguchi analysis of circular profile multihole Cu electrode
Taguchi analysis is used for the selection of bestoptimized parameter value for the individual process parameter and to measure the influence of each parameter at different levels.
3.1.1 Dominance of input constraints on MRR
The ANOVA main effect plot for data means shows the effect of an individual parameter at a different level of MRR. For the measurement of MRR, larger is better (S/N) was utilized because the maximum value of MRR means the higher rate of production. Therefore, for the measurement of MRR, ‘Larger is better’ ratio is used.
ANOVA response table (MRR)
Levels  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

1  0.05067  0.02700  0.04900  0.03800 
2  0.06700  0.05967  0.05367  0.06467 
3  0.04400  0.07500  0.05900  0.05900 
Delta  0.02300  0.04800  0.01000  0.02667 
rank  3  1  4  2 
Levels of selected input variables at maximum MRR
Factor  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

Level  2  3  3  2 
Rank  3  1  4  2 
3.1.2 Influence of input constraints on EWR
The ANOVA main effect plot for data means indicate the effect of an individual parameter at a different level of EWR (electrode wear rate). For the measurement of EWR, Smaller is better (S/N) was utilized because the minimum value of EWR means the higher accuracy of production and tool life. Therefore, for the measurement of EWR, ‘Smaller is better’ ratio is used.
ANOVA response table (EWR)
Levels  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

1  0.000407  0.000300  0.003233  0.000300 
2  0.002933  0.000053  0.000053  0.002987 
3  0.000000  0.002987  0.000053  0.000053 
Delta  0.002933  0.002933  0.003180  0.002933 
Rank  4  2.5  1  2.5 
Levels of selected input variables at minimum EWR
Factor  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

Level  3  2  2  1 
Rank  4  2.5  1  2.5 
3.1.3 Dominance of input parameters on circularity
The ANOVA main effect plot presents the effect of an individual parameter at the different level of form tolerance namely circularity. For the measurement of circularity, smaller is better (S/N) was utilized because the minimum value of circularity deviation means the higher precision and accuracy. Therefore, for the measurement of circularity, ‘Smaller is better’ ratio is used.
ANOVA response table (circularity)
Levels  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

1  0.03283  0.22103  0.05617  0.02140 
2  0.04907  0.03693  0.03073  0.20843 
3  0.21583  0.03977  0.21083  0.06790 
Delta  0.18300  0.18410  0.18010  0.18703 
rank  3  2  4  1 
Levels of selected input variables for circularity
Factor  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

Level  1  2  2  1 
Rank  3  2  4  1 
3.1.4 Dominance of input parameters on cylindricity
The ANOVA main effect plot is showing the effect of an individual parameter at a different level of Cylindricity tolerance. For the measurement of cylindricity form tolerance, smaller is better (S/N) ratio was used because the minimum value of cylindricity deviation means the highest precision and accuracy. Therefore, for the measurement of cylindricity, ‘Smaller is better’ ratio is used.
ANOVA response table (cylindricity)
Levels  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

1  0.04030  0.04853  0.05270  0.02397 
2  0.05360  0.02553  0.04110  0.02797 
3  0.02750  0.04733  0.02760  0.06947 
Delta  0.02610  0.02300  0.02510  0.04550 
Rank  2  4  3  1 
Levels of selected input variables for cylindricity
Factor  DIA of multihole electrode  Peak current (I_{p})  Pulse on time (T_{on})  Dielectric fluid pressure 

Level  3  2  3  1 
Rank  2  4  3  1 
4 Multiparametric optimization using the Grey relational method
The steps used for multiparametric optimization using the Grey relational analysis are discussed below [40, 41]:
(b) Calculation for the Grey relational coefficients:
(c) Calculation for the Grey relational grade:

α_{j} = Grey relational grade

m = No. of execution grade characteristics.
Calculated values for normalization, Grey relational coefficient and grades
Sr. nos.  Normalization  Grey relational coefficients  Grades  

MRR  EWR  Circularity  Cylindricity  MRR  EWR  Circularity  Cylindricity  
1.  0  0.89772727  0.95678337  0.575609756  0.33333333  0.830188679  0.920443102  0.540897098  0.656216 
2.  0.703296703  0.98181818  0.997811816  0.948780488  0.62758621  0.964912281  0.995642702  0.907079646  0.873805 
3.  0.868131868  0.98181818  0.920495988  0.341463415  0.79130435  0.964912281  0.862806797  0.431578947  0.762651 
4.  0.461538462  1  0.888767323  0  0.48148148  1  0.818019093  0.333333333  0.658208 
5.  0.648351648  1  0.980853392  1  0.58709677  1  0.963119073  1  0.887554 
6.  1  0  0.916666667  0.379268293  1  0.333333333  0.857142857  0.446137106  0.659153 
7.  0.32967033  1  0  0.98902439  0.42723005  1  0.333333333  0.978520286  0.684771 
8.  0.516483516  1  0.873997082  0.457317073  0.50837989  1  0.798718322  0.479532164  0.696658 
9.  0.505494505  1  1  0.887804878  0.50276243  1  1  0.816733068  0.829874 
Grey relational grade response table
Process parameters  Level 1  Level 2  Level 3 

A  0.73497  0.76423  0.73710 
B  0.66639  0.81934  0.75256 
C  0.67068  0.77833  0.78729 
D  0.79121  0.73924  0.70584 
Average Grey relational grade = 0.74543 
(e) Selection of the optimal levels of process parameters by taking the highest values of levels for each parameter from the optimum level table. The Response table is clearly indicating the level values for process parameters. The highest value of process parameters for each parameter showed the bestoptimized value.
(f) Confirmation of experiment and verification of the optimized process parameters.
4.1 Confirmation of experiment
Confirmation of experiment
Predicted value  Experimentation  

Level  A_{1}B_{1}C_{2}D_{2}  A_{2}B_{2}C_{3}D_{1} 
MRR  0.067  0.062 
EWR  0.00016  0 
Circularity  0.0112  0.0205 
Cylindricity  0.0135  0.0093 
Grade  0.87381  0.88755 
Improvement in Grey relational grade: 0.01374 
5 Fuzzy logic modelling for performance predictions
Selected linguistic variables for fuzzy model
Input  Range  

Parameter  Linguistic variable  
A (electrode hole DIA.)  Small (S), medium (M), large (L)  0.08–0.24 
B (I_{p})  Low (L), medium (M), high (H)  4–12 
C (T_{on})  200–600  
D (dielectric fluid pressure)  0.1–0.3 
Output  Range  

Parameter  Linguistic variable  
Material removal rate (MRR)  Very low (VL), Low (L), avg., good, excellent  0.003–0.094 
Electrode wear rate (EWR)  Very low (VL), avg., high (H), very high (VH)  0–0.0088 
Form tolerance deviation (circularity)  Very low (VL), low (L), medium (M), high (H), Very high (VH)  0.01–0.5583 
Form tolerance deviation (cylindricity)  very low (VL), low (L), medium (M), high (H), very high (VH)  0.0093–0.0913 
5.1 Structure of fuzzy rules
 1.
If (Electrode hole DIA. is Small) and (I_{p} is L) and (T_{on} is L) and (Dielectric fluid pressure is L) then (MRR is VL) (EWR is H) and (Circularity is Avg.) and (Cylindricity is Avg.).
 2.
If (Electrode hole DIA. is Small) and (I_{p} is M) and (T_{on} is M) and (Dielectric fluid pressure is Avg.) then (MRR is Good) (EWR is Avg.) and (Circularity is VL) and (Cylindricity is VL).
 3.
If (Electrode hole DIA. is Small) and (I_{p} is H) and (T_{on} is H) and (Dielectric fluid pressure is H) then (MRR is Excellent) (EWR is Avg.) and (Circularity is L) and (Cylindricity is H).
 4.
If (Electrode hole DIA. is M) and (I_{p} is L) and (T_{on} is M) and (Dielectric fluid pressure is H) then (MRR is Avg.) (EWR is L) and (Circularity is L) and (Cylindricity is VH).
 5.
If (Electrode hole DIA. is M) and (I_{p} is M) and (T_{on} is H) and (Dielectric fluid pressure is L) then (MRR is Good) (EWR is L) and (Circularity is VL) and (Cylindricity is VL).
 6.
If (Electrode hole DIA. is M) and (I_{p} is H) and (T_{on} is M) and (Dielectric fluid pressure is Avg.) then (MRR is Excellent) (EWR is VH) and (Circularity is L) and (Cylindricity is Avg.).
 7.
If (Electrode hole DIA. is Large) and (I_{p} is L) and (T_{on} is H) and (Dielectric fluid pressure is Avg.) then (MRR is Avg.) (EWR is L) and (Circularity is VH) and (Cylindricity is VL).
 8.
If (Electrode hole DIA. is Large) and (I_{p} is M) and (T_{on} is L) and (Dielectric fluid pressure is H) then (MRR is Avg.) (EWR is L) and (Circularity is L) and (Cylindricity is Avg.).
 9.
If (Electrode hole DIA. is Large) and (I_{p} is H) and (T_{on} is M) and (Dielectric fluid pressure is L) then (MRR is Avg.) (EWR is L) and (Circularity is VL) and (Cylindricity is VL).
5.2 Accuracy of fuzzy model’s
Comparison of Fuzzy model and experimental results
Sr. nos.  Input parameters  Output parameters  

A  B  C  D  MeasuredMRR  Predicted MRR (fuzzy model)  Error %  Accuracy %  Measured form tolerance  Predicted form tolerance (fuzzy model)  Error %  Accuracy %  
1.  0.16  4  400  0.3  0.045  0.0445  1.11  98.88  0.071  0.06  15.49  84.50 
2.  0.24  8  200  0.3  0.05  0.0485  3.00  97  0.0791  0.071  10.24  89.75 
3.  0.24  12  400  0.1  0.049  0.0485  1.02  98.98  0.01  0.0095  5  95 
Accuracy of model = 94.01% 
6 Results and conclusion
The EDM process parameter for Nibased superalloy (Inconel718) has been optimized by Taguchi analysis and multiobjective optimization method GRA to obtain an optimal solution. The optimized parameters for the response of MRR, EWR and form tolerance are: Ø 0.16 mm DIA. of the multihole electrode, 8 Amps I_{p}, 600 µs T_{on} and 0.1 kg/m^{2} dielectric fluid pressure. The optimal solutions have been calculated from output responses. An attempt has also been made to attain the Max. and Min. Evaluation of MRR and form tolerances respectively. The attained outcomes had also been examined through a real experiment and established to be satisfactory. The experimental results showed considerable advancement in the process. From Taguchi analysis, the obtained results are: For MRR, I_{p} and dielectric fluid pressure are the most significant constraints, whereas the T_{off} has the least significance. The MRR improves with an increase in spark discharge area which is higher for the multihole electrode. For EWR, DIA. of a hole in the multihole electrode is the most influencing parameters, whereas the T_{on} has the least significance. T_{on} and I_{p} are the most influencing constraint for circularity, whereas the DIA. of the multihole electrode has less significance. For cylindricity form tolerance, Dielectric fluid pressure is the most influencing parameter, whereas the T_{on} has less significance.
The utilization of a multihole electrode improves the MRR as well as the form tolerances and minimizes the EWR. The Fuzzy model has been developed to measure the output results. The accuracy and percentage of the model is 96.45% respectively. This model may be used to predict the accurate output responses (MRR, EWR and form tolerance) of Nibased superalloy. The attained optimal outcomes had been tested by conducting a real experiment trial and found to be acceptable. Therefore, these experimental results will facilitate the aerospace and defence industries to improve the productivity, performance and MRR of Inconel718 superalloy with closer tolerances.
Notes
Compliance with ethical standards
Conflict of interest
The authors declare that the have no Conflict of interest.
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