International Journal on Mechanical Engineering and Robotics (IJMER)
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Comparative Analysis of Surface Roughness of Untreated H-11 Die Steel and Deep Cryogenic Treated Steel Machined by WEDM
1Sandeep Kumar, 2Rakesh Bhatia
1Assistant professor Guru Kashi University, Talwandi Sabo, Bathinda
2Assistant professor Yadavindra College of Engineering, Talwandi sabo
Abstract - Deep Cryogenic treatment (“DCT”) is a supplementary process to improve the properties of metals like H-11 die steel which are commonly used in manufacturing of high-performance cutting tools (Dies and Punches), blanking and punching tools, extrusion tools, parts of aerospace and automotive industries, etc. The purpose of this study is to compare and investigate the effect of most significant parameters of WEDM like pulse on, pulse off time and peak current on surface roughness over H-11 die steel which is cryo-treated and untreated.
Taguchi based technique is applied by latest software MINITAB in order to reveal results by L9 orthogonal array has been applied to conduct experiments and statistically evaluate the experimental data by analysis of variance (ANOVA technique). It is investigated that surface roughness of cryo-treated samples decreases and microstructure became more refined than untreated samples.
Keywords - DCT, ANOVA, MINITAB, WEDM.
I. INTRODUCTION
WEDM is a non-traditional machining process controlled by a number of process parameter such as Pulse on time, Pulse off time, Peak current, discharge frequency and Wire tension. For optimal machining performance the setting of various input parameters plays a vital role on output parameters. In present work an attempt is made to compare and investigate the effect of varying pulse on time, pulse off time and Peak current on untreated and cry-treated H-11 Die steel in order to analyze effect on the surface by using ANOVA analysis and multi response Taguchi base optimization will be carried out [1]. A Taguchi design of experiment (DOE) approach with L9 Orthogonal Array employed to conduct this experiment. MINITAB 15 is used to perform the ANOVA (analysis of Variance) [2].
Material is eroded from the work piece by a series of discrete sparks between the work piece and the wire electrode (tool) separated by a thin film of dielectric fluid which is continuously force fed to the machining zone to flush away the eroded particles [3]. In Wire electric discharge machining (WEDM) the thin copper wire (diameter is 0.05-0.25 mm) is used as electrode.
The cutting process only applies on condition that working piece is a conductive electricity material and it
will not influenced by the hardness and toughness of work piece [4]. This process had actively developed and extensively applied to the hard, fragile and difficult- cutting material, especially to complicated form and small piece of working piece [5-9].
II. EXPERIMENTAL PROCEDURE
A. Material specification
H-11 Die steel has been used as a work piece material for the present experiments. H-11 is special hot-worked chromium tool-steel with good hardness and toughness properties. It is used for extreme load conditions such as hot-work forging, extrusion etc. It has varied practical applications such as manufacturing of punching tools, mandrels, mechanical press forging die, plastic mould and die-casting dies, aircraft landing gears, helicopter rotor blades and shafts [6-7].H-11 die steel material has been heated to a temperature of approximate 8000C with half an hour soak time followed by quenching in a salt bath to obtain a final hardness of 55 HRC.
The working life and dimensional accuracy of H-11 steel dies and tools can be improved with this suitable heat treatment, and afterward heat treated material is further given a special treatment named “Deep cryogenic treated” in order to improve the mechanical and micro structural properties of the material.
The DCT (Deep cryogenic treated) process having temperature range between -1850C to -1900C with complete cycle of 35 hours. Setup for cryo treatment is shown in Figure 1.1
The chemical composition of this material as obtained by EDAX (Electro Dispersive X-ray Spectroscopy) test is given in Table 1.1.
Figure 1.1 Setup for Cryogenic Treatment
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Table 1.1 Chemical Composition of the material Constituent Composition (%)
C 0.28
Si 0.81
Mn 0.35
P 0.011
S 0.008
Cr 4.9
Mo 1.2
V 0.85
B. Number of reading optimization based on Taguchi method
Input parameters varied during the experimentation are pulse on time (Ton) and pulse off time (Toff) and peak current (I). The effects of these input parameters are studied on wear behavior. The levels for various control factors over WEDM machine can be taken as shown in table 1.2
Following are the parameter selected for experimentation which had most significant factors and having significant affect over the WEDM process and levels for the experimentation were decided by Taguchi methodology are:-
Pulse on time (Ton),
Pulse off time (Toff),
Peak current (I).
Table 1.2 Levels for various control factors Control
factor
Symbol Level 1
Level 2 Level 3
Pulse on time (Ton)
A 115 118 121
Pulse off time (Toff)
B 50 52 54
Peak current (I)
C 160 170 180
C. Experimental setup
Experimental work over cryo-treated and untreated samples H-11 die steel is carried out by varying three control factors by applying L9 orthogonal array under DOE by Taguchi methodology. Specimens were prepared on WEDM machine (ELEKTRA SPRINTCUT 734) of Electronica Machine Tools Ltd. installed at Central Tool Room Ludhiana (Punjab), by using brass wire electrode of 0.25 mm diameter.
D. Specimen detail
In present work total 9 experiments has been carried out on Cryogenic Treated specimen and untreated specimen of geometrical dimensions 30 mm x 8 mm x 8 mm of H- 11 die steel. Finally prepared specimens for testing and analysis purpose are shown in figure 1.2 (a) & 1.2 (b) by the WEDM under suitable selected parameters.
Figure 1.2 (a) Cryogenic treated Specimens Lying Horizontally.
Figure 1.2 (b) Untreated Specimens Lying Vertically.
E. Surface Roughness
Roughness is a measure of the texture of a surface. It is quantified by the vertical deviations of a real surface from its ideal form. If these deviations are large, the surface is rough; if small, the surface is smooth. It measures average roughness by comparing all the peaks and valleys to the mean line, and then averaging them all over the entire cut-off length. Cut-off length is the length that the stylus is dragged across the surface; a longer cut-off length will give a more average value, and a shorter cut-off length might give a less accurate result over a shorter stretch of surface. Surface roughness measurements in μm were repeated two times using a Mitutoyo’s surftest, a portable surface roughness tester and the average value was considered as surface roughness value for the analysis purpose.
Figure 1.3 Set Up for Surface Roughness Measurement.
In this work the surface roughness is measured by Mitutoyo's surftest SJ-201P (Figure 1.3). The work pieces are attached to the detector unit of the SJ-201P
which traces the minute irregularities of the work piece surface. The vertical stylus displacement during the trace is processed and digitally displayed on the liquid crystal display of the SJ-201P. The surftest has a resolution varying from .01 μm to 0.4 μm depending on the measurement range. The dimensions of the samples, cut from the material blank, were measured by a Mitutoyo’s digital micrometer having a least count of 0.001mm. Both samples HT and CT put under the stylus of surftest and three readings are taken for each sample.
III. ANALYSIS AND RESULTS
A. DOE Analysis
Response surface methodology (RSM) is a technique that can be used to develop, improved and optimized process using a collection of statistical and mathematical techniques. This method has been applied in product development activities as well as improvement to the existing product. RSM is used in industry to analyze several input variables that will influence performance or quality characteristic of the product or process. The performance or quality characteristic is known as a response. The analysis of response data is done by well known software "MINITAB 15" specifically used for the design of experiment applications.
Table 1.3 Trials for Surface Roughness of CT samples.
Exp.Run Ton Toff I Trials for Surface Roughness
(A) (B) (C) SR1 SR2 SR3 MEAN
1 1 1 1 3.31 3.94 3.11 3.45
2 1 2 2 3.09 3.08 3.05 3.07
3 1 3 3 3.41 3.52 3.21 3.38
4 2 1 2 2.9 4.17 3.07 3.38
5 2 2 3 2.82 4.17 3.51 3.50
6 2 3 1 2.85 3.1 3.38 3.11
7 3 1 3 2.78 3.16 3.26 3.07
8 3 2 1 3.25 3.67 4.03 3.65
9 3 3 2 3.11 3.28 3.61 3.33
From the table 1.3 it is observed that the minimum value of surface roughness for Cryogenic Treated sample is obtained as 3.07 µm. The optimum value is obtained at 1-2-2 orthogonal array designed by Taguchi technique the values of control factors Pulse on time (Ton), Pulse off time (Toff) and Peak Current (I) is 115 µ, 52 µ and 170 Amp respectively.
B. Performance Predictions for Surface Roughness For Cryogenic Treated Samples.
The normal probability plot is a graphical technique used for assessing whether or not a data set is approximately normally distributed. The points on this plot form a nearly linear pattern, which indicates that the normal distribution is a good model for this data set. The normal probability plot showed the set of value of response variables are very close to median of set of values and not deviate from mid value, therefore the data is normally distributed. Figure no. 1.4 is shown below; give the normality plot for selected response variable as Surface Roughness of CT samples which is normal distributed because set of values of all three response are mostly close to mid value.
4.0 3.5 3.0 2.5
2.0 99
95 90 80 70 60 50 40 30 20 10 5
1
CT
Percent
Mean 3.189 StDev 0.2572
N 9
A D 0.437
P-Value 0.226 Probability Plot of CT
Normal - 95% CI
Figure 1.4 Normal Probability plot of SR.
Response table for signal to noise ratio and response table for means were generated by using Minitab 15 software are shown below.
Table 1.4 Response table for Signal to Noise ratios (Smaller is better)
Level Ton Toff I
1 -
10.38 - 10.42
- 10.66
2 -
10.52 - 10.67
- 10.31
3 -
10.50 - 10.31
- 10.44 Delta 0.14 0.36 0.35
Rank 3 1 2
3 2 1 -10.3 -10.4 -10.5 -10.6 -10.7
3 2 1
3 2 1 -10.3 -10.4 -10.5 -10.6 -10.7
Ton
Mean of SN ratios
Toff
I
Main Effects Plot for SN ratios Data Means
Signal-to-noise: Smaller is better
Figure 1.5 Main effects plot for S/N ratio Table 1.5 Response Table for Means for Surface
Roughness.
Level Ton Toff I
1 3.302 3.300 3.404
2 3.330 3.408 3.262
3 3.350 3.274 3.316
Delta 0.048 0.133 0.142
Rank 3 2 1
3 2 1 3.40 3.35 3.30 3.25
3 2 1
3 2 1 3.40 3.35 3.30 3.25
Ton
Mean of Means
Toff
I
Main Effects Plot for Means Data Means
Figure 1.6 Main effects plot for Means.
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Also it is observed the response table 1.5 shown above gives the means for surface roughness of cryogenic treated samples which is minimum at A1, B3 and C2 levels where the response factors are Pulse On Time (Ton) 115 µ, Pulse off time (Toff) 54 µ and Peak current (I) 170 Amp, the affect of response factors is shown in main effects plot for means in figure 1.6.
After obtaining the optimum level for control factors corresponds to significant parameters ANOVA is calculated as shown in table 1.6 by using Minitab 15 software.
Table 1.6 ANNOVA Table for Mean Data of Surface Roughness
Source DF Seq. SS Adj.SS MS F P
Ton 2 0.003454 0.003454 0.001727 0.01 0.987
Toff 2 0.030047 0.030047 0.015023 0.11 0.900
I 2 0.030973 0.030973 0.015486 0.11 0.897
Error 2 0.270610 0.270610 0.135305
Total 8 0.335084
DF - degrees of freedom, Seq. SS - sum of squares, Adj.SS – adjusted sum of squares, MS - mean squares (Variance), F-fitted mean, P- Percentage Contribution indicates the significance of the input factor.
The optimum value of surface roughness for Cryogenic Treated samples is obtained as 3.06 µm.
By using Minitab 15 software Predicted values for S/N ratio, Mean Standard Deviation and Linear standard deviation are calculated as shown in table 1.7 and corresponding the factor levels for prediction are shown in table 1.8
Table 1.7 Predicted Values S/N
Ratio
Mean St. Dev Ln (St. Dev) -10.4274 3.31074 0.422247 -0.552988
Table 1.8 Factor levels for prediction Pulse on time
(Ton)
Pulse on time (Toff)
Peak current (I)
3 µ 1 µ 3 Amp
C. Performance Predictions for Surface Roughness of Heat Treated Samples.
For surface roughness of HT samples, trails were carried out by taking three set of readings as shown under column SR1, SR2 and SR3 of table 4.1 with the help of surface roughness tester (Mitutoyo surftest SJ-201P).
Mean of trials is calculated to get optimum value of surface roughness.
Table 1.9 Trials for Surface Roughness of HT Samples From table 1.9 it is observed that the minimum value of surface roughness for Heat Treated sample is obtained as 3.08 µm. The optimum value is obtained same at 1-1- 1 and 1-2-2 orthogonal array designed by Taguchi technique the values of control factors Pulse on time (Ton), Pulse off time (Toff) and Peak Current (I) is 115 µ, 50 µ and 160 Amp and 115 µ, 52 µ and 170 Amp respectively.
4.5 4.0
3.5 3.0
2.5 99
95 90 80 70 60 50 40 30 20 10 5
1
HT
Percent
Mean 3.543 StDev 0.2572
N 9
AD 0.197
P-Value 0.838
Probability Plot of HT Normal - 95% CI
Figure 1.7 Normal Probability plot of SR.
Table 1.9 Trials for Surface Roughness of HT samples Exp. Run Ton Toff I Trials for Surface Roughness
(A) (B) (C) SR1 SR2 SR3 MEAN
1 1 1 1 3.03 3.13 3.08 3.08
2 1 2 2 3.11 3.05 3.08 3.08
3 1 3 3 3.48 3.43 3.46 3.46
4 2 1 2 3.31 3.16 3.24 3.24
5 2 2 3 3.9 4.03 3.97 3.97
6 2 3 1 3.28 3.75 3.52 3.52
7 3 1 3 3.95 3.7 3.83 3.83
8 3 2 1 4.2 3.4 3.8 3.80
9 3 3 2 3.24 3.32 3.28 3.28
Table 2.0 Response Table for Signal to Noise Ratio for Surface Roughness (Smaller is better).
Level Ton Toff I
1 -10.11 -10.54 -10.78
2 -11.04 -11.12 -10.10
3 -11.20 -10.68 -11.47
Delta 1.10 0.58 1.37
Rank 2 3 1
3 2 1 -10.0 -10.4 -10.8 -11.2 -11.6
3 2 1
3 2 1 -10.0 -10.4 -10.8 -11.2 -11.6
Ton
Mean of SN ratios
Toff
I
Main Effects Plot for SN ratios Data Means
Signal-to-noise: Smaller is better
Figure 1.8 Main effects plot for S/N ratio of Surface Roughness
Table 2.1 Response Table for Means for Surface Roughness.
Level Ton Toff I
1 3.206 3.381 3.466
2 3.573 3.616 3.199
3 3.636 3.418 3.750
Delta 0.430 0.234 0.551
Rank 2 3 1
3 2 1 3.8
3.6
3.4
3.2
3 2 1
3 2 1 3.8
3.6
3.4
3.2
Ton
Mean of Means
Toff
I
Main Effects Plot for Means Data Means
Figure 1.9 Main effects plot for Means of Surface Roughness.
The response table 2.1 gives the means for surface roughness which is minimum at A1, B1 andC2 levels where the response factors are to be measured as Pulse on time (Ton) 115 µ, Pulse off Time (Toff) 50 µ and Peak current (I) 170 Amp, this affect is shown in main effects plot for means in figure 4.3.The Optimum value for surface roughness from Heat Treated samples is noted as 3.08 µm.
Table 2.2 ANNOVA Table for Mean Data of Surface Roughness
Source DF Seq.SS Adj.SS MS F P
Ton 2 0.324032 0.324032 0.162016 69.40 0.014
Toff 2 0.095425 0.095425 0.047712 20.44 0.047
I 2 0.455743 0.455743 0.227872 97.61 0.010
Error 2 0.004669 0.004669 0.002335
Total 8 0.879869
DF - degrees of freedom, Seq. SS - sum of squares, Adj.SS – adjusted sum of squares, MS - mean squares (Variance), F-fitted mean, P- Percentage Contribution indicates the significance of the input factor.
From the optimum set of response factors ANOVA is calculated in Minitab 15 software which give the following results as shown in table 2.2.
Table 2.3 Table for Predicted values S/N
Ratio
Mean St. Dev Ln (St.
Dev) -10.4274 3.31074 0.422247 -0.552988
Table 2.4 Table for Factor levels Pulse on time
(Ton)
Pulse off time (Toff)
Peak Current (I)
160 µ 118 µ 52 Amp.
IV. CONCLUSION
It is concluded that surface roughness decreases in case of cryogenic treated material which is compared with the following results as discussed under:-
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The analysis of results it was observed that cryogenic treatment had made a significant contribution in improving surface finish. The crystals homogeneity due to reduction of vacancies inside crystal lattice is the reason for this improvement. Cryogenic treatment of the work piece significantly improves the surface finish of machined surface [10].
For H-11 Material, Surface Roughness is affected by Pulse on Time. Percentage contributions of Pulse on time are more. Increasing pulse on time sustain spark for longer period so more thermal energy is generated.
Resulting craters will be broader and deeper; therefore the surface finish will be rougher [11].
All the analytical findings for the surface roughness of Cryogenic Treated materials for pulse on time are same as if compared with the results that discussed above and agreed with the improvement caused by the cryogenic treatment.
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