Optimization of process parameters of lapping operation by taguchi appr
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  • 1. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 15 OPTIMIZATION OF PROCESS PARAMETERS OF LAPPING OPERATION BY TAGUCHI APPROACH FOR SURFACE ROUGHNESS OF SS 321 Pravin R. Parate1 and Dr. Ravindra B. Yarasu2 1 PhD Student & Faculty Mechanical Engineering Department, Shri Bhagubhai Mafatlal Polytechnic, Mumbai. India 2 Associate Professor, Mechanical Engineering Department, Government College of Engineering, Amravati, India ABSTRACT Lapping is a finishing process extensively used in the manufacturing industry for those parts that require a fine finish surface such as gage blocks or flats for checking production parts. The present work is aimed at optimizing the lapping parameters for surface roughness by machining component, having outer diameter 50mm and inner diameter 45mm of SS 321 on single plate table top lapping machine. Experiments based on design of experiments were conducted varying lapping load, lapping time, paste concentration, lapping fluid and by using different types of abrasives. Statistical method of Taguchi has been used in this work. Optimum machining parameters for surface roughness are estimated and are, verified with experimental results and are, found to be in good agreement. The confirmation test exhibits good surface finish by using Al2O3 abrasive particles along with oil as a carrier fluid. Further as the lapping load increases, surface roughness decreases, whereas it increases with increase in paste concentration and lapping time. Keywords: Lapping, SS 321, Taguchi, ANOVA. I. INTRODUCTION A lapping machine usually consists of a rotating lap which can hold several work pieces at one time. The work pieces are contained within control rings that prevent work pieces from moving off the lap. Pressure cylinders are used to provide the necessary pressure for efficient cutting action. In mechanical lapping, a rotating lap is coated with abrasive slurry [1,2,3]. A weighted workpiece is placed on top of the lap and as the lap rotates, the abrasive grains cut from the workpiece surface very small chips. The workpiece is usually placed within a control ring to restrict its movement. Almost any flat surfaced workpiece can be lapped. The tooling is simple and consists mainly of an abrasively charged lap, a rotating control ring, and a weighted workpiece holder. The quality of the INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET) ISSN 0976 – 6340 (Print) ISSN 0976 – 6359 (Online) Volume 4, Issue 4, July - August (2013), pp. 15-21 © IAEME: www.iaeme.com/ijmet.asp Journal Impact Factor (2013): 5.7731 (Calculated by GISI) www.jifactor.com IJMET © I A E M E
  • 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 16 part which is being lapped is mainly determined by lapping method, type of abrasive used, addition agent, lapping tool, lapping pressure, lapping motion and premachining procedure etc. [1]. When we consider the lapping technology as a input and procedure to study is the output, the machining condition as the input and the machining quality and efficiency as the output, then the need to study the lapping technology is to define the relationship between input and output. Although the aim of lapping is to improve surface finish, sometimes parts are rejected after lapping because of burn, friction, incomplete lapping, scratches, micro voids, and wear. Scratches may be caused by excessive load, low supply of abrasive slurry, or high friction and burn may be caused by excessive load [3]. Uneven distribution of load occurs when the lapping table is not flat, but rather concave or convex in shape. Even components are affected by pressure because of which extra heat is created at the faces of the component, and the faces will get distorted [1]. So it is necessary to study the lapping technology and analyze the effect of the different process parameters such as different types of abrasives, their grain size, various carrier fluid, the lapping cycle time, abrasive concentration, load forces, and plate speed to achieve the desired surface finish, by optimizing the process parameters, so that the manufacturing industries can produce the high quality products to satisfy the needs and requirements of the customers. II. METHODOLOGY Workpiece Preparation The workpiece made of SS 321 in the form of outer diameter of 50 mm and inner diameter of 45 mm, which is shown in Figure 1. This is used for experimentation purpose as this metal is most commonly used in manufacturing industries. Figure 1. OHNS Workpiece Figure 2. Single Plate Table Top Lapping Machine Experimental Design Design of experiments (DOE) is a powerful tool that can be used in a variety of experimental situations. DOE techniques enable designers to determine simultaneously the individual and interactive effects of many factors that could affect the output results in any design. A standard Taguchi L8 (25 ) Orthogonal Array (OA) is chosen for this investigation as it can operate five parameters, each at two levels. By combining the orthogonal Latin squares in a unique manner Taguchi prepared a set of common OA’s to be used for a number of experimental situations. A common OA for 2-level five factors is shown in Table1. This format is chosen from a preliminary work, that identified five parameters (a) lapping load; (b) Paste concentration; (c) Type of abrasive; (d) Lapping time; (e) Lapping fluid, as important lapping variables which affect the finishing rate
  • 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 17 (Evans C.J. et al., 2003; Chung Chunhui, 2011; Kang J. et al 2001). Lapping speed has been kept constant. Taguchi method stresses the importance of studying the response variation using the signal – to – noise (S/N) ratio, resulting in minimization of quality characteristic variation due to uncontrollable parameter. The surface roughness is considered as the quality characteristic with the concept of "small-the-better". The S/N ratio used for this type response is given by (Taguchi, 1987) S/N = -10log10 (mean of sum of squares of measured data) Table 1. L8 (25 ) Orthogonal Array Experiment Column 1 2 3 4 5 1 1 1 1 1 1 2 1 1 1 2 2 3 1 2 2 1 1 4 1 2 2 2 2 5 2 1 2 1 2 6 2 1 2 2 1 7 2 2 1 1 2 8 2 2 1 2 1 The experiments were carried out with five factors at two levels each, Table 2. The fractional factorial design used is a standard L8 (25 ) orthogonal array. This orthogonal array is chosen due to its capability to check the interactions among factors. The machining has been carried out and the experimental data for the surface roughness values and the calculated signal-to-noise ratio are shown in Table 3. Table 2. Test Run Design Experiment 1 2 3 4 5 1 3.3 1.65:5 Al2O3 10 Oil 2 3.3 1.65:5 Al2O3 15 Kerosene 3 3.3 1.65:10 SiC 10 Oil 4 3.3 1.65:10 SiC 15 Kerosene 5 6.6 1.65:5 SiC 10 Kerosene 6 6.6 1.65:5 SiC 15 Oil 7 6.6 1.65:10 Al2O3 10 Kerosene 8 6.6 1.65:10 Al2O3 15 Oil Table 3. Experimental results for surface roughness and its calculated S/N ratios Experiment No. 01 02 03 04 05 06 07 08 Surface Roughness (µm) 0.257 0.213 0.414 0.434 0.403 0.247 0.274 0.319 S/N LTB (dB) 11.80 13.43 7.66 7.25 7.89 12.15 11.25 9.92
  • 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 18 III. LEVEL AVERAGE RESPONSE ANALYSIS The level average response analysis is based on averaging the experiment results achieved at each level for each parameter. When performing level average response analysis for one level of one parameter, all the influences from different levels of other parameters will be counterbalanced because every other parameter will appear at different level once. So the effect of one parameter at one level on the experiment results can be separated from other parameters. In this way, the effect of each level of every parameter can be viewed independently. Table 4, shows that, as the lapping load increases, surface roughness decreases, whereas it increases with increase in paste concentration. Further, a good surface finish is achieved after using Al2O3 abrasives and oil as a lapping fluid. Surface roughness increase drastically by using SiC abrasive particles and considerably by using kerosene as a lapping fluid. Table 4. Level Average Response for Surface Roughness (µm) Parameters Levels Test Run Surface Roughness (µm) Level Average Response (µm) Parameter A Lapping Load Level 1 3.3 Kg 1 0.257 0.330 2 0.213 3 0.414 4 0.434 Level 2 6.6Kg 5 0.403 0.311 6 0.247 7 0.274 8 0.319 Parameter B Type of Abrasives Level 1 Al2O3 1 0.257 0.266 2 0.213 7 0.274 8 0.319 Level 2 SiC 3 0.414 0.375 4 0.434 5 0.403 6 0.247 Parameter C Lapping Time Level 1 10 min 1 0.257 0.337 3 0.414 5 0.403 7 0.274 Level 2 15 min 2 0.213 0.303 4 0.434 6 0.247 8 0.319 Parameter D Paste Concentration Level 1 1.65:5 1 0.257 0.280 2 0.213 5 0.403 6 0.247 Level 2 1.65:10 3 0.414 0.360 4 0.434 7 0.274 8 0.319 Parameter E Lapping Fluid Level 1 Oil 1 0.257 0.309 3 0.414 6 0.247 8 0.319 Level 2 Kerosene 2 0.213 0.331 4 0.434 5 0.403 7 0.274
  • 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 19 IV. ANALYSIS OF VARIANCE (ANOVA) Analysis of variance is a computational technique to quantitatively estimate the relative contribution, which each controlled parameter makes to the overall measured response and expressing it as a percentage. Thus the information about how significant the effect of each controlled parameter is on the experimental results can be obtained. ANOVA uses S/N ratio responses to calculate. The overall mean from which all the variation (standard deviation) is calculated is given by S/Nሬሬሬሬሬሬሬሬറ = 1/n ∑ S/N୬ ଵ i. Table 5, shows the results of ANOVA analysis. Table 5. ANOVA Results Symbol Parameter Sum of Squares Contribution A Lapping Load 0.150 0.39 % B Type of Abrasive 13.382 42.30 % C Lapping Time 2.154 5.56 % D Paste Concentration 10.562 27.27 % E Lapping Fluid 0.366 0.95 % Error 23.53 % Total 100 % Grand Total Sum of Square (GTSS) = 865.697 Sum of the square due to overall mean SSmean= 827.268 Sum of the squares due to variations around overall mean SSvariation = 38.429 V. CONFIRMATION EXPERIMENT In order to validate the results obtained, the confirmation experiments were conducted by utilizing the levels of the optimal process parameters, for surface roughness value on single plate table top lapping machine, the optimum machining parameters as shown in Table 7 and results obtained and compared with predicted values are shown in Table 8. The optimal conditions are set for the significant factors and a selected number of experiments are run under specified cutting conditions. The average of the results from the confirmation experiment is compared with the predicted average based on the parameters and levels tested. Table 7. Confirmation Experiments Experiment 1 2 3 4 5 1 3.3 Al2O3 05 min 1.65:5 Oil 2 3.3 Al2O3 07 min 1.65:5 Oil Table 8. Experimental Results Experiment No. 1 2 Surface Roughness (µm) 0.257 0.245
  • 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 20 VI. CONCLUSION The influences of individual lapping parameters on the surface roughness can be clearly seen and observed that, increase in lapping load, and by using kerosene as a carrier fluid, hampers the surface finish. One can achieve the surface finish by using Al2O3 abrasive particles along with oil as a carrier fluid, under low pressure. Further increasing the paste concentration and changing the abrasive from Al2O3 to SiC, cause to decrease the surface finish of the component. This concludes that type of abrasive particles and paste concentration plays an important role. From the findings of the following can be concluded: 1. Taguchi’s robust design method is suitable to optimize the surface roughness 2. The significant factors for surface roughness are Type of Abrasive with contribution of 42.3 %, Paste Concentration with 27.27 % and Lapping time with contribution of 5.56 %. VII. ACKNOWLEDGEMENT The authors would like to thank Principal and Staff of Mechanical Engineering Department, Government College of Engineering, Amravati, Principal, S.B.M. Polytechnic Mumbai, IIT Mumbai and Le-con Industries, Mumbai for their valuable support. REFERENCES Journal Papers [1] Kang J. and Hadfield M. 2001 Parameter optimization by Taguchi Methods for finishing advanced ceramic balls using a novel eccentric lapping machine Journal of Engineering Manufacture, Vol 215. [2] Evans C. J., Paul E., Dornfeld D.,Lucca D.A., Byrne G., Tricard M., Klocke F. 2003 Material Removal Mechanism in Lapping and Polyshing Precision Manufacturing Group, UC Berkeley. [3] Chung Chunhui 2011 Experimental Study and Modeling of Lapping Using Abrasive Grits with Mixed Sizes Journal of Manufacturing Science and Engineering Volume 133, Issue 3. [4] Dhole N.S., Naik G.R., Prabhawalkar M.S., Optimization of Milling Process Parameters of EN33 using Taguchi parameter Design Approach Journal of Engineering Research and Studies JERS/Vol III/Issue I/ January-March 2012. [5] Ascanio Gabriel, Cava Carlos 2007 Improved Single Face lapping by using an Air Bearing supported Lap Journal of Applied Research and Technology, Vol.5, No.3. [6] Guo Huairui and Metass Adamantios 2011 Design of Experiments and Data Analysis Realibility and Maintainability Symposium. [7] Kamaruddin S., Khan Zahid A, 2010 Application of Taguchi Method in the Optimization of Injection Moulding parameters for Manufacturing Products from Plastics Blend IACSIT International Journal of Engineering and Technology, Vol.2, No.6. [8] Kang J. and Hadfield M. 2005 The effects of lapping load in finishing advanced ceramic balls on a novel eccentric lapping machine Journal of Engineering Manufacture, Vol. 219. [9] Rao Rama, Padmanabhan G 2012 Application of Taguchi methods and ANOVA in Optimization of Process Parameters for MRR in ECM of Al5%SiC Composites International Journal of Engineering Research and Applications (IJERA), Vol.2, Issue3. [10] Vermal Jitendra, Agarwal Pankaj, Bajpai Lokesh 2012 Turning Parameter Optimization for Surface Roughness of ASTM A242 Type-1 Alloys Steel By Taguci Methods International Journal of Advances in Engineering and Technology, March 2012.
  • 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 21 [11] Zhang Zefang, Liu Weili and Song Zhitang 2010 Effect of abrasive particle concentration on preliminary chemical mechanical polishing of glass substrate Journal of Microelectronic Engineering, Volume 87, Issue 11. [12] Zhang Zefang, Liu Weili and Song Zhitang 2011 Influence of pH and abrasive concentration on polishing rate of amorphous Ge2Sb2Te5 film in chemical mechanical polishing Journal of Vaccum Science and Technology, Volume 29, Issue1. [13] Zhongqi Wang 1996 The Precision Lapping Techniques of Engineering Ceramics Transactions of Tianjin University, Volume2, No.1. [14] Taguchi G, Hocheng, 1987 Taguchi methods orthogonal arrays and linear graphs, tools for quality engineering. Dearborn, MI: American Supplier Institute, pp. 35 - 38. [15] Vishal Francis, Ravi.S.Singh, Nikita Singh, Ali.R.Rizvi and Santosh Kumar, “Application of Taguchi Method and Anova in Optimization of Cutting Parameters for Material Removal Rate and Surface Roughness in Turning Operation”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 4, Issue 3, 2013, pp. 47 - 53, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359. [16] Ajeet Kumar Rai, Richa Dubey, Shalini Yadav and Vivek Sachan, “Turning Parameters Optimization for Surface Roughness By Taguchi Method”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 4, Issue 3, 2013, pp. 203 - 211, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359. [17] Vipin Kumar Sharma, Qasim Murtaza and S.K. Garg, “Response Surface Methodology & Taguchi Techquines to Optimization of C.N.C. Turning Process”, International Journal of Production Technology and Management (IJPTM), Volume 1, Issue 1, 2010, pp. 13 - 31, ISSN Print: 0976- 6383, ISSN Online: 0976 – 6391. Books [1] Bagchi T. P., 1993 Taguchi methods explained: practical steps to robust design Prentice Hall of India Pvt. Ltd., New Delhi.