Puttur, Andhra Pradesh, India , Andhra Pradesh, India ,

Transcription

1 th International & th All India Manufacturing Technology, Design and Research Conference (AIMTDR ) December th th,, IIT Guwahati, Assam, India OPTIMIZATI OF DIMENSIAL DEVIATI:WIRE CUT EDM OF VANADIS- E (POWDER METALLURGICAL COLD WOKRED TOOLSTEEL) BY TAGUCHI METHOD D.Sudhakara * G.Prasanthi * Dept. of Mechanical Engineering, Siddartha Institute of Science& Technology, Puttur, Andhra Pradesh, India-73, sudhakara@gmail.com Dept. of Mechanical Engineering, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India-, dr.smt.g.prasanthi@gmail.com Abstract: Wire electrical discharge machining is the trendiest advanced manufacturing process to manufacturer sophisticated components, moulds and dies with very good dimensional accuracy. The main aim of this experimental work is to find out optimal process parameters to reduce dimensional deviation as compared to required dimensions. The process parameters of this Wire electrical discharge machining is pulse on time, pulse off time, peak current, spark gap set voltage, wire tension and water pressure.the orthogonal array of L 7 Taguchi design is used to plan conduct the experiments. The ANOVA is employed to find out the effects of process parameters on dimensional accuracy. The process parameters are optimized in order to minimize the output response i.e. dimensional deviation. The VANADIS E (powder metallurgical cold worked tool steel) is used for experimental work and the experiments are conducted on WEDM set up of ELECTRICA ULTIMA-F. Key words: Wire electrical discharge machining, VANADIS E (powder metallurgical cold worked tool steel), Taguchi method, Dimensional Deviation, ANOVA. INTRODUCTI: WEDM is a most popular modern manufacturing process in the present manufacturing industry[]. The mechanism of metal removal is similar to that of conventional EDM process, in which the erosion effect is produced by series of electrical sparks between work piece and wire electrodes which are surrounded by di electric fluid. During wire electrical discharge machining a large amount of temperature of C - C is developed in the form of thermal energy after applying voltage between wire electrode and work piece. When the discharge occurs, a small amount of material is melted and removed from the work piece surface. The continuously supplying di electric fluid flushes the derbies formed during machining. A wire made of copper or brass is used as wire electrode and it is continuously supplied through work piece. To eliminate the stress between wire electrode and work piece, the wire should travel at a small distance away from the work piece. A mechanical tensioning device is used to produce tension in the wire electrode while is travelled through the work piece[3]. The wire EDM can be successfully used to cut any conductive and high strength temperature resistance material irrespective of their hardness, shape and toughness [,7]. Several researchers have been worked to obtain optimal solution of process parameters for getting higher dimensional accuracy (less dimension deviation) is not yet fully solved. In the present research study WEDM of VANADIS E(Powder metallurgical cold worked tool steel) has been considered. This material is considered for research work due to its both high wear resistance and ductility. VANADIS E is a chromium-molybdenum-vanadium alloyed steel which is characterised by very ductility, high abrasive- adhesive wear resistance and compressive strength, good dimensional stability during heat treatment in service, good machine ability and grind ability. The main chemical composition of VANADIS E is C-.%, Si-%,Mn-%,Cr-.7%,Mo-3.% and Va-3.% and the balance is Fe. The density of VANADIS E is 77kg/m 3. LITERATURE SURVEY Speeding and Wang [997] performed experimental study on AISI steel to optimize the process parameters in combinations by modelling the process using ANN and characterised the WEDM machined surface by time series technique.kanlayasiri et.al.[7] started investigation of the effects of machining parameters on surface roughness of WEDM machining of DC3cold die steel with Sodic model A. The machining variables included were pulse on time, pulse peak current, pulse off time and wire tension. The variables effecting on the surface roughness were identified by ANOVA 9-

2 OPTIMIZATI OF DIMENSIAL DEVAITI: WIRE CUT EDM OF VANADIS- E (POWDER METALLURGICAL COLD WOKRED TOOLSTEEL) BY TAGUCHI METHOD technique. The assumptions of ANOVA were tested by residual analysis. From the results it showed that pulse on time and pulse peak current were significantly affected the surface roughness. 3 EXPERIMENTAL SET UP, PREPARATI OF SPECIMENS AND EXPERIMENTAL DESIGN The Vanadis E Tool steel plate of mm x 9mm x mm size is mounted on the ELECTRICA ULTIMA F WEDM machine tool and specimens of 7mmx7mmxmm size are cut. conducted to select the range of values for machining parameters.the orthogonal array of L 7 Taguchi design is used to plan conduct the experiments. Table Process parameters, their values and ranges PROCESS SYM UNITS PARAMETES BOL Pulse On Time µsec Pulse Off Time µsec Peak Current Amp Spark gap set SV Volts Voltage Wire Tension WT Grams Water Pressure WP Kg/cm RESULT ANALYSES L L L The 7 experiments were conducted on the work piece as per L 7 orthogonal array(oa) in order to find out the effect of machining parameters on dimensional deviation. Table Experimental results for dimension deviation with cutting conditions in the Table as per L7 orthogonal array (OA) FigureWork piece Mounted on WEDM FigurePieces lying horizontal after WEDM In the present study six parameters pulse on time, pulse off time, peak current, Spark gap set Voltage, wire tension and water pressure weree selected as input parameters during machining of work piece. The Experiments were conducted with distilled water as di-electric fluid and its conductivity is S, Servo feed is m/min, wire feed as m/min with a coated brass wire of. mm diameter as electrode. The six parameters were assigned values in 3 levels based on trail experiments. The preliminary experiments were Exp no R R R3 S/NRatio

3 th International & th All India Manufacturing Technology, Design and Research Conference (AIMTDR ) December th th,, IIT Guwahati, Assam, India The average values of dimensional deviation for each parameter level, and 3 for raw data and S/N data are shown in figure 3 and figure.the figure 3 and figure reveals that the dimensional deviation first decreases effectively and then increases slightly with increase in pulse on time. Thedimensional deviation is increases with increase in pulse off time and then decreases strongly. The peak currentincreases, the decreases in dimensional deviation steeply as it is concluded from the results. When the increase in water pressure, the dimensional deviation increases due to the large amount of force act on the wire electrode. Due to these forces the wire electrode fluctuatesand the dimensional deviation will come in to the picture.the effect of spark gap set voltage and wire tension are not very significant as compares to the other process parameters. The dimensional deviation is increased, with increase in energy contained in the pulse. So that when the pulse on time increases then dimensional deviation will also increases. Mean of SN ratios 3 Signal-to-noise: Smaller is better Main Effects Plot (data means) for SN ratios A B C D E F Figure Effects of Process Parameters on dimensional deviation (S/N Data) Interaction Plot for SN ratios Data Means Main Effects Plot (data means) for Means Signal-to-noise: Smaller is better Mean of Means.7..7 A B C D E F Figure Effects of Process Parameters Interactions on dimensional deviation (S/N Data). Interaction Plot for Means Data Means Figure 3 Effects of Process Parameters on dimensional deviation (Raw Data) Figure Effects of Process Parameters Interactions on dimensional deviation (Raw Data 3 9-3

4 OPTIMIZATI OF DIMENSIAL DEVAITI: WIRE CUT EDM OF VANADIS- E (POWDER METALLURGICAL COLD WOKRED TOOLSTEEL) BY TAGUCHI METHOD Percent Frequency Percent Frequency Normal Probability Plot - Histogram - Residual Plots for Means Versus Fits Fitted Value Versus Order Observation Order Figure 7 Residual Plots for dimensional deviation (Raw Data) - - Normal Probability Plot - Histogram Residual Plots for SN ratios Versus Fits Fitted Value Versus Order Observation Order Figure Residual Plots for Cutting Rate (S/N Data). It also clear from the interaction plots for means and (interaction plots for S/N Ratio) as shown in figure and, there is moderate interaction between pulse on time and pulse off time, pulse off time and peak current in effecting the dimensional deviation. The interaction between pulse on time and peak current is weak because the interactions are almost parallel.residual plots are drawn to find out the data for the problems like non normality,non random variation, non constant variance, higher order relationships. The residuals versus fitted values indicated a little tendency for a variance of the residuals to increase as the dimensional deviation values increases. The problem however, is not severe enough to have any dramatic impact on the analysis and conclusions. The normal probability plot, histogram plot, and residual versus observation order plot of these residuals do not reveal any problem.. Selection of optimum Levels In order to study the significance of the process parameters towards the dimensional deviation, ANOVA was performed. It was found that wire tension and water pressure are non significance process parameters for dimensional deviation. Non Significance parameters were pooled and the pooled versions of ANOVA of the S/N data and raw data for dimensional deviationare given in table 3 table and table respectively. Table 3 Pooled Analysis of Variance for (S/N ratios) Analysis of Variance for SN ratios Source DF Seq SS Adj SS Adj MS F P A B C F Residual Error Total 7. Table : Response Table for Signal to Noise Ratios Response Table for Signal to Noise Ratios Smaller is better Level A BCF Delta Rank 3 Table Pooled Analysis of Variance for Means (Raw data) Analysis of Variance for Means Source DF Seq SS Adj SS Adj MS F P A B.3..9 C F Residual Error.3 Total.33 Table Response Table for Means Response Table for Means LevelA B CF Delta Rank 3 9-

5 th International & th All India Manufacturing Technology, Design and Research Conference (AIMTDR ) December th th,, IIT Guwahati, Assam, India From these table 3&, it is clear that pulse on time,pulse off time, peak current and water pressure significantly affect both the mean and variation in the dimensional deviationvalues. The response tables & show that the average of each response characteristics ( S/N data and Means) for each level of each factor. The tables include ranks based on delta statistics, which compare the relative magnitude of effects. The delta statistics is the highest minus the lowest average for each factor. MINITAB assigns ranks based on delta values; rank to the highest value, rank to the second highest, and so on. The rank indicates relative importance of each factor to the response. The ranks and delta values show that pulse on time have the greatest effect on dimensional deviationand is followed by, pulse off time, peak current and water pressure in that order. As the dimensional deviation is the smaller is better type quality characteristics, it can be seen from figure 3 that the nd level of pulse on time (A), 3 rd level of pulse off time(b3), 3 rd level of peak current(c3) and st level of water pressure(f) provide the maximum value of dimensional deviation. The S/N data analysis also reveals that same level of the variable (A, B3, C3 and F) as the best levels for minimum dimensional deviationin Wire cut EDM process...estimation of Optimum response characteristics: In this section, the optimal values of the response characteristics dimensional deviationalong with their respective confidence intervals have been predicted. The results of confirmation experiments are also presented to validate the optimal results. The optimal levels of the process parameters for the selected response characteristics have already been identified. The optimal value of each response characteristic is predicted considering the effect of the significant parameters only. The average values of the response characteristics obtained through the confirmation experiments must lie within the 9% confidence interval, CI CE equation. However, the average values of quality characteristics obtained from the confirmation experiments may or may not lie within 9% confidence interval, CI POP (calculated for the mean of the population).. Dimensional Deviation: The optimum value of dimensional deviationis predicted at the optimal levels of significant variables which have already been selected as pulse on time (A), pulse off time(b3), peak current (C3) and spark gap set voltage (F). The estimated mean of the response characteristic (DD) can be determined as: µ T = overall mean of dimensional deviation= ( R+ R+ R3)/ =.9 % A = average value of dimensional deviational the third level of pulse on time = 7 % B3 average value of dimensional deviational the first level of pulse off time = 77% C3 = average value of dimensional deviational the third level of peak current =.3999% F = average value of dimensional deviational the first level of water pressure= 3% Substituting the values of various terms in the above equation, µ = (.9) =.% The 9 % confidence intervals of confirmation experiments ( ) and population ( ) are calculated by using the following Equations., and, Where, F α (, ) = The F ratio at the confidence level of (-α) against DOF and error degree of freedom f e. n eff =N/+(DOF associated in the estimation of mean response) n= = 9, N= Total number of results= 7x3= and R= Sample size of confirmation experiments=3 and = Error variance =.3 From table () and = error DOF = F. (, ) =.39 (Tabulated F-value, Roy 99). So, = ± 3and, ±. Therefore, the predicted confidence interval for confirmation experiments is: Mean - < < Mean <µ <. The 9% confidence interval of the population is: 9-

6 OPTIMIZATI OF DIMENSIAL DEVAITI: WIRE CUT EDM OF VANADIS- E (POWDER METALLURGICAL COLD WOKRED TOOLSTEEL) BY TAGUCHI METHOD Mean < < Mean +.3 <µ <.33 The optimal values of process variables at their selected levels are as follows: Second level of pulse on time (A) :µs Third level of pulse off time (B3) : 3 µs Third level of peak current (C3) : 3 amps First level of Water pressure (F) : kg/cm.3 CFIRMATI EXPERIMENT In order to validate the results obtained, three confirmation experiments were conducted for the response characteristics (dimensional deviation) at optimal levels of the process variables. The average values of the characteristics were obtained and compared with the predicted values. The results are given in Table 7. The values of dimensional deviationobtained through confirmation experiments are within the 9% of of respective response characteristic. It is to be pointed out that these optimal values are within the specified range of process variables. Table 7 Predicted Optimal Values, Confidence Intervals and Results of Confirmation Experiments Performance Measures/ Responses Dimensional Deviation Optimal Set of Parameters Predicted Optimal Value A,B3,C3,F.% Predicted Confidence Intervals at 9% Confidence Level Actual Value (Average of Three Confirmation Experiments) =-.33< <. =.3<µ <.33.% CCLUSIS The effects of machining parameters on dimensional deviationwith wire electric discharge machining (WEDM) process has been studied with the aim of minimization of dimensional deviationusing Taguchi s design. An optimal set of machining process variables that yields the optimum quality features to machined parts produced by WEDM process has also been obtained. The important conclusions from the present research work are summarized in this chapter. References. M. N. Islam, N. H. Rafai, and S. S. Subramanian (),An Investigation into Dimensional AccuracyAchievable in Wire-cut Electrical DischargeMachining,Proceedings of the World Congress on Engineering Vol. III, London, U.K.. Puri A.B., and Bhattacharyya B., An analysis and optimization of the geometrical inaccuracy due to wire lag phenomenonin WEDM, Int. J. Mach. Tools Manuf. 3(): 9(3). 3. Ho, K.H. and Newman, S.T.,(), State of art in wire electrical discharge machining (WEDM), Int. J. Mach. Tools Manuf. : 7 9. Kansal, H.K., Sehijpal, S., and Pradeep K., Technology and research developments in powder mixed electric discharge. Ranges of Wire EDM process parameters have been established based on review of literature and by performing the trail run experiments using one factor at a time approach.the optimum wire EDM process parameters were obtained to get minimum dimension deviation i.e. A, B3, C3,F.From the results it is concluded that, pulse on time(a), pulse off time(b), peak current(c), water pressure (F) are the most influencing factors in WEDM machining of VANADIS E and Spark gap set Voltage (D) wire tension (E) are the non significant factors when comparison to the factors mentioned above. machining (PMEDM). J. Mater. Process. Technol : 3 (7).. Ramasawmy, H, Blunt. Effect of EDM process parameterson 3D surface topography. J Mater Process Technol : ().. Spedding, T. A., Wang, Z.Q. (997), Parametric optimization and surface characterization of wire electrical discharge machining process, Precision Engineering, (), - 7. Kanlayasiria, K., Boonmung, S. (7), Effects of wire-edm machining variables on surface roughness of newly developed DC 3 die steel: design of experiments and regression model, Journal of Materials Processing Technology, 9-93,