Optimization of Radial Force in Turning Process Using Taguchi s Approach

5 th International & 6 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 04) December th 4 th, 04, IIT Optimization of Radial Force in Turning Process Using Taguchi s Approach Sumit verma *, Hari Singh * M.Tech. Scholar, Mechanical Engineering Department, National Institute of Technology, Kurukshetra 369, India, sumitverma0087@gmail.com Professor, Mechanical Engineering Department, National Institute of Technology, Kurukshetra, 369, India, hsingh_nitk@rediffmail.com Abstract Efficient turning of high performance EN series material can be achieved through proper selection of turning process parameters to minimize radial force. Cutting parameters are optimized to minimize radial force in turning of EN-8 steel using carbide inserts as cutting tool. The experiments are conducted using L8 orthogonal array as an experimental design. The cutting parameters are optimized using signal to noise ratio and the analysis of variance. The effects of nose radius, spindle speed, feed rate and depth of cut are analyzed. The confirmation tests are carried out at optimum cutting conditions. Optimal values of process parameters for desired performance characteristic are obtained by Taguchi s approach. The main effect plot (figure ) shows the low feed rate and low depth of cut result in minimum value of the radial force i.e., 36.58 N. Table 4 reveals that all the factors i.e., nose radius, spindle speed, feed rate and depth of cut are the significant factors in affecting the radial force at 95% confidence level. Keywords: Turning operation, EN-8 steel, radial force, Taguchi s approach. Introduction In today s scenario, the most important thing which is considered is the value of a product. Value, as defined, is the ratio of function to cost. Value can therefore be increased by either improving the function or reducing the cost. The function can be improved by improving the quality and the quality should be produced into the product at the design stage instead of controlling quality at the manufacturing stage or through the inspection of final products. Taguchi s method can be applied for optimization of process parameters to produce high quality products with lower manufacturing costs. Improving the quality could be achieved by optimizing the turning process. In turning process, there are mainly three components of cutting forces which are tangential force, feed force and radial force. In a competitive industrial atmosphere, there is need to decrease the cutting forces because the lower cutting forces have several advantages such as lower power consumption, improvement in surface finish, low stress components, burr-free surfaces, better dimensional accuracy, and better part quality. Taguchi is regarded as the foremost proponent of robust parameter design, which is an engineering approach for product development or process design that focuses on minimizing variation and sensitivity to noise. Taguchi s parameter design is one of the important tools for robust design, which offers a systematic approach for parameters optimization in terms of performance, quality and cost. This robust parameter design strategy provides a powerful and efficient method for designing products and processes that operate consistently and optimally over a variety of conditions. Robust design is capable of (a) making product performance insensitive to raw material variation, thus permitting the use of lower grade alloys and components in most cases; (b) making designs robust against manufacturing variations, thus reducing labour and material cost for rework and scrap; (c) making the design least sensitive to the variation in operating condition, thus improving reliability and reducing operating cost; and (d) using a new structured development process so that engineering time is used more productively. Abdulla (994) studied the performance of six coated-carbide inserts in machining of EN4 steel. He applied response surface methodology for experimentation. Kabra et al (03) reported parametric optimization and modelling for surface roughness, feed force and radial force of EN-9/ANSI-440 steel in CNC turning using Taguchi and Regression analysis method. Recently developed tool materials such as coated carbide have improved productivity levels of difficult-to-machine materials. Lo and Chen (977) studied tool life in DC hot machining of EN4 steel using carbide tools in the speed range of 35 30 m/min. They applied response surface methodology for design of experiments. Nakayama and Shaw (967) investigated the machining of EN4 steel with HSS 76-

Optimization of Radial Force in Turning Process Using Taguchi s Approach tools and carbide tools. They investigated large forces during machining which may result in tool fracture and high cutting temperatures. Nalbant et al. (006) adopted the same methodology to find the optimal cutting parameters in turning operation based on experimental results on AISI 030 steel bars using TiN-coated tools. Roy (990) proposed Taguchi s parameter design, an important tool for robust design, which offers a systematic approach for parameters optimization in terms of performance, quality and cost. Singh and Kumar (006) used Taguchi methods for optimization of turning parameters for EN-4 steel. Yang and Tarng (998) investigated the effects of cutting speed, feed rate and depth of cut while turning of S45C steel bars using tungsten carbide cutting tools. Taguchi s technique has been used for experimental work. The improvement of tool life and surface roughness from the initial cutting parameters to the optimal cutting parameters is about 50%. Thus, Taguchi methodology can be effectively used to optimize process parameters for single performance characteristic only. The objective of this study is to obtain optimal settings of experimental parameters (nose radius, spindle speed, feed rate and depth of cut) to yield optimal radial force while machining EN-8 steel with carbide inserts. Taguchi s parameter design approach has been used to accomplish the objective. Experimental Parameters The following experimental parameters were selected for present work: (A) nose radius, (B) spindle speed, (C) feed rate and (D) depth of cut. The work material selected in this investigation is EN-8. The chemical composition of the alloy includes: C, 0.36-0.45%; Si, 0.05-0.35%; Mn, 0.60.0%; S, 0.06%; P, 0.060%. EN-8 steel is a medium strength steel which is suitable for manufacturing of stressed pins, shaft studs and keys. Tensile properties can vary but are usually between 500-800 N/mm². EN-8 is widely used for applications which require better properties than mild steel. EN-8 can be flame or inductions hardened to produce a good surface hardness with moderate wear resistance. A commercial available EN-8 steel rod having diameter 7mm was used for performing turning experiments. The turning experiments were performed on a centre lathe of H.M.T. The input power supply to the machine is three phase ac 45 V. The operating frequency is 50 Hz. The control voltage for the machine is 0 V and the rated current is 3 A. The cutting tools selected for this experimentation are the carbide inserts. All the descriptions regarding the inserts are: insert geometry: CCMT 0 6 0 (ISO designation) and Nose radii: 0.4 mm, 0.8 mm. 3 Selection of orthogonal array (OA) An experiment was designed using Taguchi method proposed by Roy, R. K., (990), who used an orthogonal array to study the entire parametric space. Before finalizing a particular OA for this purpose of designing the parameters the following two things must be established (a) the number of levels for the parameters of interest, (b) the number of parameters and their interaction of interest. In the present study the four machining parameters considered are: nose radius, cutting speed, feed rate and depth of cut. Nose radius was set at two different levels while other parameters were set at three different levels. The process parameters and their values are given in table. Table Factors and Levels Symbol Factor Levels Level Level Level 3 A Nose 0.4 0.8 radius (mm) B Spindle 3 490 75 930 speed (rpm) C Feed rate 3 0.04 0.08 0.6 (mm/rev) D Depth of cut (mm) 3 0.60 0.80.00 In present case, L8 orthogonal array was selected for the study. The total degrees of freedom for three parameters each at three levels and one parameter at two levels are 7. And total degree of freedom for the L8 is 7. Therefore, an L8 orthogonal array is used. The L8 orthogonal array is shown in table. 4 Experimental Analysis EN-8 steel rods of 7mm diameter and 500mm length were turned on a centre lathe of H.M.T. Carbide inserts were used to machine EN-8 steel. Three specimens for each trial condition were prepared using randomization technique. Thus 54 specimens were turned and a customized dynamometer was used to measure the radial force. The dynamometer was capable of taking readings in kgf. The readings have been converted into newtons. 76-

5 th International & 6 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 04) December th 4 th, 04, IIT Table Experimental layout using L8 orthogonal array Trial no. Nose Radius Cutting Speed Feed Rate Depth of Cut 3 3 3 4 5 6 3 3 7 3 8 3 3 9 3 3 0 3 3 3 4 3 5 3 6 3 3 7 3 8 3 3 The selected quality characteristic for radial force is lower the better type and the signal to noise ratio (S/N) for lower the better type of response was used as given in equation (): S N = 0 log0 () n n y i i= where n is number of replications and y i is the observed response value of quality characteristics for a trial condition where i=,...n. The S/N ratios were calculated using Eq. () for each of the 8 trials and the values are reported in table 3 along with the raw data value. R, R and R3 are the replications and are from three different experiments. The mean response refers to the average value of the performance characteristic for each parameter at different levels. The average values of radial force for each parameter at different levels are computed and shown in figure. The average values of S/N ratios of various parameters at different levels are plotted in figure. It is evident from the figure that radial force is minimum at the first level of feed rate and the first level of depth of cut. Also it can be seen that spindle speed at the second level favours reduction of radial force. The effect of nose radius is not very clearly defined but higher nose radius is suitable for the radial force. In table 3, the mean value and S/N ratio are determined using the MINITAB software. Table 3.Experimental results for Radial force and S/N ratio Trial No. Radial Force (N) Radial Force Radial Force R R R3 Mean Value (N) S/N Ratio (db) 9.4 34.3 39.9 34.34333-30.776 88.6 98.06 88.6 9.5667-39.4 3 7.49 7.49 7.9 4.09-4.883 4 39.4 49.08 43.35 43.95-3.8944 5 78.45 88.6 88.6 84.99-38.600 6 98.06 07.9 07.9 04.33-40.366 7 73.45 78.45 88.6 80.05333-38.093 8 7.7 37.9 7.47 7.4933-4.68 9 0.9 0.9 0.9 0.9-40.49 0 83.35 83.35 88.6 84.98667-38.590 58.86 58.86 63.35 60.35667-35.698 0.9 0.9 98.06 0.933-40.38 3 58.86 58.86 68.68 6.3333-35.8905 4 07.87 98.06 98.06 0.33-40.38 5 88.6 78.45 88.6 84.99-38.600 6 68.67 68.67 78.45 7.93-37.56 7 68.67 68.67 68.67 68.67-36.7353 8 98.06 88.6 98.06 94.79333-39.5459 Average 84.6696-38.45 76-3

Optimization of Radial Force in Turning Process Using Taguchi s Approach Table 4 Analysis of Variance (raw data) Mean of Means 00 90 80 Nose Radius Main Effects Plot for Means Data Means Spindle Speed Feed Rate Depth of Cut Source DOF SS V F P % A 665.4 665.4 6.78 0.0.04 B 3.3 566.4 5.77 0.006 3.47 C 437.5 763.7 73.0 0.000 43.89 D 004.6 600.3 6. 0.000 36.78 E 46 453.6 98. 3.83 T 53 3643.4 70 Table 5 Analysis of Variance (S/N ratio) 60 3 3 3 Figure Effect of process parameters on radial force (raw data) Mean of SN ratios -35-36 -37-38 -39-40 Nose Radius Signal-to-noise: Smaller is better Main Effects Plot for SN ratios Data Means Spindle Speed Feed Rate Depth of Cut 3 3 3 Figure Effect of process parameters on radial force (S/N ratio) Thus second level of nose radius, second level of spindle speed, first level of feed rate and first level of depth of cut represent the optimal levels of various turning process parameters to yield an optimal value of the radial force. In order to quantify the influence of process parameters on the selected machining characteristics, analysis of variance (ANOVA) was performed. The ANOVA for the raw data (radial force) is given in table 4. It shows that all the factors are significant in affecting the response. The order of significance of these parameters is feed rate, depth of cut, spindle speed and nose radius. The percent contribution of parameters for radial force reveals that the influence of feed rate in affecting the radial force is significantly larger followed by depth of cut, spindle speed and nose radius. Also the ANOVA for the S/N ratio for radial force are reported in table 5. Source DOF SS V F P % A 0.94 0.94 0.0 0.760 0.3 B 6.36 3.8.6 0.45 4.3 C 65.633 3.87 6.8 0.00 44.6 D 55.333 7.667 4. 0.00 37.6 E 0 9.578.9578 3.3 T 7 47. where SS = sum of squares, DOF = degrees of freedom, V = variance, e = error, T = total, F 0.05; (, 46) =4.057 5 Estimation of Optimum Value of Radial Force The optimal radial force is predicted at the selected optimal setting of process parameters. The significant parameters with optimal levels for radial force are A, B, C, D. The calculated mean of the response characteristic can be computed for radial force using equation (): µ RF = A +B +C +D - 3T RF () where T RF = overall mean of radial force = 84.664 A = average value of radial force at the second level of nose radius in N = 8.5 B = average value of radial force at the second level of spindle speed in N = 80.5 C = average value of radial force at the first level of feed rate in N = 6.88 D = average value of radial force at the first level of depth of cut in N = 65.87 Hence, µ RF = 36.58 N A confidence interval for the predicted mean on a confirmation run can be computed using equation (3):..=, + (3) where, = F ratio required for α, α = risk, f e = 76-4

5 th International & 6 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 04) December th 4 th, 04, IIT error DOF, V e = error variance. N eff = effective no. of replication = R = number of repetitions for confirmation experiment, N= total number of experiments. Using the values V e = 98. and f e = 46 from table 4, the confidence interval was calculated. Total DOF associated with the mean (µ RF ) = +++ = 7 Total trials = 8, N = 3x8 = 54 N eff = 54/8 = 6.75, α = 0.05, F 0.05; (,46) = 4.057 (tabulated) The calculated C.I. is : C.I. = ±3.774 The predicted mean of radial force is : µ RF = 36.58 N. The 95% confidence interval of the predicted optimal radial force is: [µ RF - C.I.]< µ RF < [µ RF + C.I.] i.e.,.384< µ RF (N)<49.93. 6 Confirmation Experiments The confirmation experiment is the final step in verifying the conclusions drawn based on Taguchi s parameter design approach. The optimum setting conditions are set for the significant factors and a selected number of tests are run under constant specified conditions. The average of the confirmation experiment results is compared with the anticipated average based on the parameters and levels tested. The confirmation experiment is a critical step and is highly recommended by Taguchi to verify the experimental conclusions. Three confirmation experiments were conducted at the optimal settings of experimental parameters recommended by the investigation. The average value of radial force while turning EN-8 steel was found to be 43.784N. These results are within the 95% confidence interval of the predicted optimal values of the selected machining characteristics. Hence, the optimal settings of the process parameters as predicted in the analysis can be implemented.. The optimal settings of various process parameters for turned parts to yield optimal radial force are: nose radius = 0.8 mm; spindle speed = 75 rpm; feed rate = 0.04 mm/rev. and depth of cut = 0.60 mm. 3. The predicted optimal range (95% C.I.) of radial force is:.384< µ RF (N)<49.93. References Abdulla, A. A. (994), Performance of some coated carbide inserts in machining of EN4 steel, PhD thesis, University of Roorkee, Roorkee. Kabra, A. Aggarwal, A., Aggarwal, V., Goyal S. and Bangar, A. (03), Parametric Optimization & Modelling for Surface Roughness, Feed and Radial Force of EN-9/ANSI-440 Steel in CNC Turning Using Taguchi and Regression Analysis Method, International Journal of Engineering Research and Applications (IJERA). Vol. 3, Issue, January - February, pp.537-544. Lo, K. C. and Chen, N. S. S. (977), Prediction of tool life in hot machining of alloy steels, Int. J. Prod. Res.5: pp. 47 63. Nakayama, K. and Shaw, M. C. (967), Machining high strength materials, Ann. CIRP 5: pp. 456 459. Nalbant, M., Gökkaya, H., and Sur. G. (007) Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning. Materials & design 8, no. 4: 379-385. Roy, R. K. (990) "A primer on Taguchi method (New York: Van Nostrand Reinhold) ". Singh, H. and Kumar P. (006), Optimizing feed force for turned parts through the Taguchi technique. Sadhana 3, no. 6: 67-68. Yang, W. H., and Tarng, Y. S. (998) Design optimization of cutting parameters for turning operations based on the Taguchi method. Journal of Materials Processing Technology 84, no. : -9. 7 Conclusions The following conclusions can be concluded from this study:. The percent contribution of parameters in affecting variation in radial force while machining En-8 steel with carbide inserts are: feed rate (43.890%); depth of cut (36.775%); spindle speed (3.468%); and nose radius (.038%). 76-5