Available online at www.sciencedirect.com ScienceDirect
Procedia Materials Science 6 ( 2014 ) 1303 – 1311
3rd International Conference on Materials Processing and Characterization (ICMPC 2014) Metal Removal and Kerf Analysis in Abrasive jet drilling of Glass Sheets
D.V. Srikantha, Dr. M. SreenivasaRaob
a Associate Professor, Department of Mechanical Engineering, Abhinav Hi-Tech College of Engineering, Hyderabad, A.P.India bP rofessor, Dept. of Mechanical Engineering, JNTUH, Kukatpally, Hyderabad, A.P. India.
Abstract
Drilling of glass with different SOD’s, Pressures and different Nozzle Diameters have been carried out by Abrasive Jet Drilling process (AJD) in order to determine its mach inability under different controlling parameters of the AJM process. Abrasive jet machine (AJM) removes material through the action of focused beam of abrasive laden gas. Micro abrasive particles are propelled by an inert gas of velocity. When directed at a work piece, the resulting erosion can be used for cutting, etching, drilling, polishing and cleaning. In this paper optimization of process parameters of Abrasive Jet Machining of glass by Taguchi methodology is presented. The Values obtained in Taguchi Analysis was compared with the Analysis of Variance (ANOVA).Various levels of Experiments are conducted using L9 Orthogonal Array for both MRR and KERF. © 2014 TheElsevier Authors. Ltd. PublishedThis is an byopen Elsevier access Ltd. article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the Gokaraju Rangaraju Institute of Engineering and Technology (GRIET). Selection and peer review under responsibility of the Gokaraju Rangaraju Institute of Engineering and Technology (GRIET)
Key Words: Abrasive Jet Machining, Erosion rate, Glass, AJD, SOD, Pressure.L9orthogonal Array.
1. INTRODUCTION
In Abrasive Jet Machining, fine abrasive particles (typically ~0.025mm) are accelerated in a gas stream (commonly air) towards the work surface. As the particles impact the work surface, they cause small fractures, and the gas stream carries both the abrasive particles and the fractured (wear) particles away. A high-velocity jet of dry air, nitrogen, or carbon dioxide Containing abrasive particles is aimed at the work piece surface under controlled conditions. The jet velocity is in the range of 150-300 m/s and pressure is from two to ten times atmospheric pressure. Abrasive Jet Machining is used for drilling, deburring, etching, and cleaning of hard and brittle metals, alloys, and non-metallic materials (e.g., germanium, silicon, glass, ceramics, and mica). No heat is required in the process of machining a piece with an abrasive jet. As a result, parts from an assembly do not experience structural changes from overheating. There are no toxic wastes given off by abrasive water jets, and no oils are necessary in the process of machining. Aluminium oxides, silicon carbides, Boron Carbides, Crushed glass, Sodium bicarbonate, Dolomite are Various Abrasive Particles used for Machining in Abrasive Jet Machining. Re use of abrasives is not recommended since the cutting ability of abrasive decrease after the usage and also the contamination of wear materials clogging the nozzle and the cutting unit orifice. The Major Process Parameters that affects the MRR in AJM are 1. Gas Pressure 2. Velocity of Abrasive Particles 3. Abrasive mass flow rate 4. Mixing ratio 5. Nozzle Tip Distance.
______
D.V.Srikanth Tel: +919703050004 E-mail Address: [email protected].
2211-8128 © 2014 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer review under responsibility of the Gokaraju Rangaraju Institute of Engineering and Technology (GRIET) doi: 10.1016/j.mspro.2014.07.109 1304 D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311
Fig 1: Line Diagram of Abrasive Jet Machining Process
2. LITERATURE REVIEW
Till date there has been a through and detailed experimental study on the Machining of Glass. El-Domiaty et al (2009) are conducted the experimentation on drilling of Glass with AJM. The abrasive grits (sand) were mixed with air stream ahead of the nozzle and the abrasive flow rate was kept constant throughout the machining process. The Results was represented with Graphs. Bhaskar Chandra Kandpal et al (2011) conducted Experimentation on machining of Glass and Ceramics with various types of Abrasives by changing pressure, nozzle tip distance on different thickness of glass plates and ceramic plates. The effect of process parameters of compared with theoretical results.Stephen Wan et al. (2010) present simple deterministic process models for the prediction of the evolution of the cross-sectional profile of glass channels generated by erosive wear in micro air abrasive jet machining using a round nozzle. Experiments were carried out on soda lime and borosilicate glass to verify the process models. Predicted model results show fairly good agreement with experimental results. Lingyin et al (2001) investigated the abrasive jet machining characteristics of a glass-infiltrated alumina used for fabrication of all-ceramic dental crowns were investigated using a high-speed dental hand piece and diamond burs with different grit sizes. Apart from the Experimental works detailed theoretical studies are also performed on Abrasive Jet Machining.Most of the studies argue over the hydro dynamic characteristics of abrasive jets, hence ascertaining the influence of all operational variables on the process effectiveness including abrasive type, size and concentration, impact speed and angle of impingement. Other papers found new problems concerning carrier gas typologies, nozzle shape, sizeand wear, jet velocity and pressure, standoff distance (SOD) or nozzle tip distance (NTD). These papers express the overall process performance in terms of material removal rate, geometrical tolerances and surface finishing of work pieces, as well as in terms of nozzle wear rate. Finally, there are several significant and important papers which focus on either leading process mechanisms in machining of both ductile and brittle materials, or on the development of systematic experimental statistical approaches, Analysis and artificial neural networks to predict the relationship between the settings of operational variables and the machining rate and accuracy in surface finishing. In recent years abrasive jet machining has been gaining increasing acceptability for drilling applications. 3. METHODS: 3.1.Design of Experiments (DOE) Experimental design is a useful complement to multivariate data analysis because itgenerates “structured” data tables, i.e. data tables that contain an important amount of structured variation. This underlyingStructure will then be used as a basis for multivariate modelling, which will guarantee stable and robust models.TheDOETechnique helps to study many factors simultaneously and most economically. By studying the effects of individualFactors on the results, the best factor combination can be determined. 3.2. Optimization based on TAGUCHI approachis used to achieve more efficient cutting parameters. According to Roy.R.K (2001), Jurkovic.Z (2009),Jurkovic. Z (2010) and Cukor.G (2011)Parameter design is the key step in the Taguchi approach to achieve high quality without increasing cost. To solve this problem Taguchi approach uses a special design of orthogonal arrays where the experimental results are transformed into the S/N ratio as the measure of the quality characteristic deviating from the desired value.
3.3.Analysis of Variance (ANOVA)
Analysis of variance (ANOVA) and F-test (standard analysis) are used to analysis the experimental data as given follows
Notation: Following Notation are used for calculation of ANOVA method C.F. = Correction factor T = Total of all result n = Total no. of experiments ST = Total sum of squares to total variation. D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311 1305
Xi = Value of results of each experiments (i = 1 to 27) SY = Sum of the squares of due to parameter Y (Y = P, S, A, T) NY1, NY2, NY3 = Repeating number of each level (1, 2, 3) of parameter Y XY1, XY2, XY3 = Values of result of each level (1, 2, 3) of parameter Y FY= Degree of freedom (D.O.F.) of parameter of Y fT = Total degree of freedom (D.O.F.) fe = Degree of freedom (D.O.F.) of error terms VY = Variance of parameter Y Se = Sum of square of error terms Ve = Variance of error terms FY = F-ratio of parameter of Y SY’ = Pure sum of square CY= Percentage of contribution of parameter Y Ce = Percentage of contribution of error terms CF = T2/n ST = ∑i=1 to 27 Xi2 – CF SY = (XY12/NY1 + XY22/NY2 + XY32/NY3) – CF fY = ( number of levels of parameter Y) – 1 fT = ( total number of results)-1 fe = fT - ∑fY VY = SY/fY Se = ST - ∑SY Ve = Se/fe FY = VY/Ve SY’ = SY – (Ve*fz) CY = SY’/ST * 100% Ce = (1- ∑ PY)*100%
4. EXPERIMENTAL WORK
4.1. Experimental set up:
Main machine structure of size 250x250x550 has been fabricated. Lifting mechanism parts have been machined & assembled as shown in Fig. Mixing chamber & hopper have been machined out of M.S sheet and welded. The opening for the abrasive Particles was arranged with air tight and leak proof system. The Nozzle was made of Tungsten carbide which can withstand for many operations. Nozzles are designed and fabricated in different sizes( 1 mm,2mm,3mm) .Working chamber is surrounded by transparent plastic sheets to view the progress of abrasive machining to make the machine environment friendly, exhauster with dust collecting lags are fixed.
Fig 2 : Fabricated Experimental Setup of Abrasive jet Machining
1306 D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311
The experimental work was carried on a test rig. The abrasive grits (Al2o3, Sic) were mixed with air stream ahead of the nozzle and the abrasive flow rate was kept constant throughout the machining process. The jet nozzle was made of Tungsten Carbide to carry high wear resistance and increase in Life of nozzle. Several nozzles were manufactured with different bore diameters of 1 mm, 2 mm and 3 mm. Drilling of glass sheets was conducted by setting the test rig on the parameters like Pressure,SOD,and Nozzle diameter, Abrasive flow rate.
(a)Nozzles with various diameters(b) Impingement angle of Nozzle Fig 3: Shows the Nozzles of different diameters and nozzle fixed to set up
a) CharacteristicsOfDifferentVariables
Table 1: Variables and characteristics in Abrasive jet machining
Medium Air , CO2 ,N2 Abrasive Sic, Al2O3 (of size 205μto 0μ ) Flow rate of abrasive 3 to 20 gram/min Velocity 150 to 300 m/min Pressure 2 to 8 kg/cm2 Nozzle size 0.07 to 0.40 mm Material of nozzle WC, Sapphire Nozzle life 12 to 300 hr Standoff distance 0.25 to 15 mm (8mmgenerally) Workmaterial glass, ceramics, granites. Metalsandalloysofhardmaterials like germanium, silicon etc part application Drilling, cutting, deburring,cleaning
Glass was used as a work piece material because of its homogeneous properties. The test specimens were cut into square and rectangular shape for machining on AJM unit having thickness 3mm, 4mm. In machine the initial weights of glass specimens were measured with the help of digital balance. After machining the final weights were measured with the help of digital balance to calculate the material removal rate. First the abrasive that was Sic in powder form was fed in the hopper carefully. After that compressor connections were checked. The glass specimen was properly clamped on cross slide with the help of various clamps. As the Compressor was switched on, the hopper gate valve was opened so that abrasive grains were mixed with air jet coming from the compressor and focused on the specimen with help of nozzle. Same experiments were with silicon carbide as abrasive in AJM process. Different readings were taken based on the levels of Taguchi Analysis using different process parameters (Pressure, Sod, and Nozzle diameter.). All results were analysed by Taguchi method and compared with ANOVA.
D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311 1307
5. EXPERIMENTATION, ANALYSIS & RESULTS
Experiments are conducted based on Taguchi’s method with three factors at three levels each. The values taken by a factor are termed to be levels. The factors to be studied and their levels chosen are detailed in the Table 2.
Table 2: Factors of Taguchi and Levels
Machining Parameters Level 1 Level 2 Level 3
Pressure (kg/cm2) 6 7 8
Stand Of Distance (mm) 8 9 10
Nozzle Diameter (mm) 2 3 4
5.1. Signal-To-Noise Ratio
The term signal represents the desirable value (mean) and noise represents the desirable value (mean) and the “noise” represents the undesirable value (standard deviation). So the S/N ratio represents the amount of variation presents in the quality characteristic. Depending upon the objective of the quality characteristic there can be various types of S/N ratio. Here the desirable objectives are higher values of MRR and lower values of KERF. So the Larger-the-better and Smaller the better type S/N ratios are mentioned below.
§ n · ¨ 1 ¸ ¦ y 2 (1) SN 10log ¨ i 1 i ¸ L ¨ n ¸ ¨ ¸ © ¹
§·n y2 ¨¸¦ i (2) SN 10log¨¸i 1 L ¨¸n ¨¸ ©¹
Where y is the observed data nis the number of observations and n is no of measurements in a Trail
Table 3: Experimental DesignMatrix and Results
EXPMachining Parameters No of Abrasive Jet Machining Pressure Sod N D MRRI MRR II SNRA1MEAN1KERFSNRA2
1 6 8 2 0.0432 0.0402-27.6141 0.04170 3.1 -9.8272 2 6 9 3 0.0441 0.0513 -26.5039 0.047703.5 -10.8814 3 6 10 4 0.0812 0.0800 -21.8740 0.08060 6.2 -15.8478 4 7 9 4 0.0637 0.0612 -24.09460.062454.1 -12.2557 5 7 10 2 0.0371 0.0298 -29.66750.033454.8 -13.6248 6 7 8 3 0.0765 0.0745 -22.4433 0.075503.6-11.1261 7 8 10 3 0.0986 0.1000 -20.06170.099305.3 -14.4855 8 8 8 4 0.0864 0.0964 -20.8201 0.09140 5.8 -15.2686 9 8 9 2 0.0542 0.0513 -25.5654 0.052754.4 -12.8691
1308 D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311
Table 4: Response Table for Means(MRR) Level Pressure Sod Nozzle Diameter 1 0.05667 0.06953 0.04263 2 0.05713 0.05430 0.07417 3 0.08115 0.07112 0.07815 Delta 0.02448 0.01682 0.03552 Rank 2 3 1
Main Effects Plot for MRR Fitted Means
Pressure Sod 0.08
0.07
0.06
0.05
0.04 6 7 8 8 9 10
Mean Nozzle Diameter 0.08
0.07
0.06
0.05
0.04 2 3 4
Fig 4: Graphs indicates the Main Effect plot for MRR (Fitted Means)
Table 5: Response Table for Signal to Noise Ratios (Larger is better)
Level Pressure Sod Nozzle Diameter 1 -25.33 -23.63 -27.62 2 -25.40 -25.39 -23.00 3 -22.15 -23.87 -22.26 Delta 3.25 1.76 5.35 Rank 2 3 1
Main Effects Plot for SN ratios Data Means
Pressure Sod -22
-24
-26
6 7 8 8 9 10 Nozzle Diameter -22 Mean of ratios SN -24
-26
2 3 4 Signal-to-noise: Larger is better Fig 5: Graphs indicates the Effect of plots on S/N Ratio Pressure, Sod, Nozzle diameter on MRR
Table 6: Response Table for Means (KERF) Level Pressure Sod Nozzle Diameter 1 4.267 4.167 4.100 2 4.167 4.000 4.133 3 5.167 5.433 5.367 Delta 1.000 1.433 1.267 Rank 3 1 2 D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311 1309
Main Effects Plot for Means Data Means
Pressure Sod 4.5
4.0
3.5
6 7 8 8 9 10 Nozzle Diameter 4.5 Mean of Means of Mean
4.0
3.5
2 3 4
Fig 6: Graphs indicates the Main Effect plot for MRR (Data Means)
5.2. Taguchi Analysis: MRR I , MRR II,KERF versus Pressure, Sod, Nozzle DiameterPredicted values.
MRR KERF S/N Ratio Mean StDev S/N Ratio Mean -19.6920 0.10045 0.0030406 -10.5327 3.33333
Factor levels for predictions: Factor levels for predictions: Pressure Sod ND Pressure Sod ND 8 10 4 6 9 3
The effect of Individual Parameter on entire process is not effectively rated by using Taguchi Method and the Predicted values of Mean S/N Ratio, Standard deviation, Factor levels are identified. By using ANONA the contribution of Individual Parameter can be well determined. The General Linear Model of ANOVA module was employed to investigate the effect of Parameters on MRR.
5.3. General Linear Model:MRR, KERFversus Pressure, Sod, Nozzle Diameter
Factor Type Levels Values Pressure fixed 3 6, 7, 8 Sod fixed 3 8, 9, 10 Nozzle Diameter fixed 3 2, 3, 4
Table 7: Analysis of Variance for MRR using Adjusted SS for Tests
Source DF Seq ss Adj ss Adj MS F P
Pressure 2 0.0013999 0.0013999 0.0007000 9.05 0.099
SOD 2 0.0004839 0.0004839 0.0002419 3.13 0.242
Nozzle 2 0.0027317 0.0027317 0.0013658 17.67 0.054 Diameter Error 2 0.0001546 0.0001546 0.0000773
Total 8 0.0047701
S = 0.00879223 R-Sq = 96.76% R-Sq (adj) = 87.04%
1310 D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311
Table 8 : Analysis of Variance for KERF using Adjusted SS for Tests
Source DF Seq ss Adj ss Adj MS F P
Pressure 2 1.8200 1.8200 0.9100 3.00 0.250 SOD 2 3.6867 3.6867 1.8433 6.08 0.141
Nozzle 2 3.1267 3.1267 1.5633 5.15 0.162 Diameter Error 2 0.6067 0.6067 0.3033
Total 8 9.2400
S = 0.550757 R-Sq = 93.43% R-Sq(adj) = 73.74%
Table 7,8 shows Analysis of Variance for MRR and KERF. In Table (7)F Value (17.67) of the parameter indicates the Nozzle Diameter is significantly contributing more towards cutting performance. F value (3.13) of parameter indicates the Contribution of Stand-off distance is less. In Table (8) F Value (6.08) of the parameter indicates the SOD is significantly contributing more towards KERF performance. F value (3.00) of parameter indicates the Contribution of Pressure is less. The R-Square values of both MRR and KERF are nearer to 100 % .This shows the results obtained are optimal.
Fig7: Different glass Sheets drilled atdifferent Nozzlediameters, SOD’s and Pressures
CONCLUSIONS This paper presents Ample results of experiments have been conducted by changing pressure, nozzle tip distance, SOD on different thickness of glass plates. The effect of their process parameters on the material removal rate (MRR) is analysed by using Taguchi Method and compared this by using Analysis of variance ANOVA. Optimal levels of Performance Found at Larger is Better MRR was identified as Air Pressure (8 kg/cm2) SOD (10 mm) Nozzle diameter (4 mm).As per the Table (4)the ranking of parameters are Nozzle diameter, Pressure and SOD. Where it was also observed from ANOVA F-test that the same parameters of Taguchi are repeated in same order. Optimal levels of Performance Found at Smaller is Better KERF was identified as Air Pressure (6 kg/cm2) SOD (9 mm) Nozzle diameter (3 mm).As per the Table (5)the ranking of parameters are Nozzle diameter, Pressure and SOD. Where it was also observed from ANOVA F-test that the same parameters of Taguchi are repeated in same order. Therefore the results obtained by TAGUCHI are nearly matching with ANOVA results.
ACKNOWLEDGMENT
The authors here by thank the authors of the below mentioned references for their valuable contribution which enabled us make this comparison.
D.V. Srikanth and M. Sreenivasa Rao / Procedia Materials Science 6 ( 2014 ) 1303 – 1311 1311
References
A.EI-Domiaty, H.M.Abd EI –Hafez, and M.A.Shaker (2009) “Drilling of glass sheets by abrasive jet machining”, World Academy of Science, Engineering and Technology 56. A. P. Verma and G. K. Lal Publication (1984) “An experimental study of abrasive jet machining”, International Journal of Machine Tool Design and Research, Volume 24, Issue 1, pp 19-29. Bhaskar Chandra Kandpal1* Naveen Kumar2 Rahul Kumar3 Rahul Sharma4 Sagar Deswal5 Machining Of Glass and Ceramic with Alumina And Silicon Carbide in Abrasive Jet Machining, International Journal of Advanced Engineering Technology, IJAET/Vol.II/ Issue IV/October-December, 2011/251-256. Cukor, G., Jurković, Z., Sekulić, M.: Rotatable Central Composite Design of Experiments versus TaguchiMethodin the Optimization of Turning,Metalurgija/Metallurgy, 50(2011)1, 17-20. Jurković, Z., Brezočnik, M., Grizelj, B., Mandic, V.: Optimization of Extrusion Process by Genetic Algorithms and Conventional Techniques, Tehnički vjesnik/Technical Gazette 16(2009)4, 27-33. Jurković, Z., Cukor, G., Andrejcak, I.: Improving the Surface Roughness at Longitudinal Turning Using the Different Optimization Methods, Tehnički vjesnik/Technical Gazette 17(2010)4, 397-402. Ling Yina, Lewis K. Ivesa, Said Jahanmira, E. Dianne Rekowb & Elaine Rombergc Abrasive Machining Of Glass- Infiltrated Alumina With Diamond Burs Machining, Science and Technology: An International Journal Volume 5, Issue 1, 2001 pages 43-61. Marshall DB, Lawn BR, Evans AG., "Elastic/plastic indentation damage in ceramics: the lateral crack system", J Am Ceramic Society, 1982; 65(11). M L Neema and P C Pandey. 'Erosion of Glass When Act Upon by an Abrasive Jet' Proceedings of International Conference on Wear of Materials, 1977. M. Roopa Rani & S. Seshan “AJM - Process Variables and Current Applications”, Publication- Journal of Metals Materials Process, 1995 Vol.7 No. 4 PP.279-290. Roy, R.K.: Design of experiments using the Taguchi approach: 16 steps to product and process Improvement, Wiley-Interscience, New York, 2001. Ruff AW, Wiederhorn SM., "Erosion by solid particle impact"; Treat Mater Sci. Tech, 1979. R. Balasubramaniam, J. Krishnan and N.Ramakrishnan (1999), “An experimental study on the abrasive jet deburring of cross drilled holes”, Publication: Journal ofMaterials Processing Technology, Volume 91, Issues 1-3, and pp 178-182. R. Balasubramaniam, J. Krishnan and N.Ramakrishnan (2002) “A study on the shape of the surface generated by abrasive jet machining”, Publication: Journal of Materials Processing Technology, Volume 121, Issue 1, 14February 2002, pp 102-106. R.H.M. Jafar*1, M. Papini2, 1, J.K. Spelt1, 2, Numerical simulation of surface roughness and erosion rate in abrasive jet micromachining of Glass. 2013 – Elsevier. Sheldon, G.L. and Finnie, I., Trans. ASME B (J. Eng. for Industry), 1966, 88 B, 387-392. Stephen Wan, Weng Seng Fong, Qi Ying Leong-- Deterministic Process Modelling of Micro Air Abrasive Jet Machining of Glass Channel- 2010, Key Engineering Materials, 447-448, 272. U.D.Gulhani, P.P.Patkar,S.P.Patel,A.A.Patel et al ,Analysis of AJM Parameters on MRR, Kerf width of Hard and Brittle Materials like Ceramics,--IJDMT-April-2013.