OPTIMIZATION OF ABRASIVE WATER JET MACHINING PROCESS .

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International Journal of Mechanical And Production Engineering, ISSN: 2320-2092,Volume- 2, Issue-9, Sept.-2014OPTIMIZATION OF ABRASIVE WATER JET MACHINING PROCESSPARAMETERS USING TAGUCHI GREY RELATIONAL ANALYSIS(TGRA)1B. SATYANARAYANA, 2G. SRIKAR1Associate Professor, Department of mechanical Engineering, VNR VJIET, HYDERABAD-80,2Student, Department of mechanical Engineering, VNR VJIET, HYDERABAD-80,E-mail: 1sanbollu@gmail.com, 2srikar2109@gmail.comAbstract- Abrasive Water Jet Machining (AWJM) is a versatile machining process primarily used to machine hard anddifficult to machine materials. The objective of this paper is to optimize material removal rate and kerf width simultaneouslyusing AWJM process on INCONEL 718. The process parameters are chosen as abrasive flow rate, pressure, and standoffdistance. Taguchi Grey Relational Analysis is opted because of multi response optimization.Keywords- AWJM, Grey Relational Analysis, Process Parameters, S/N Ratio, And Taguchi Method.I.INTRODUCTIONAbrasive water jet (AWJ) cutting is a non-traditionalcutting process that employs high-pressure water forproducing high velocity stream, entrained withabrasive particles for a wide variety of materialsranging from soft to hard materials.Fig.1 Parameters influencing the AWJM cutting process [6]It is a versatile process that can be employed in manymanufacturing applications such as cutting, milling,cleaning, and surface treatment and offers certainunique benefits like negligible heat affected zone incutting process, high degree of maneuverability, andless machining force exertion.II.PRINCIPLEIII.LITERATURE SURVEYW. Koenig, CH. Wulf, P. Grass, H. WIllerscheid [5]found that the cut surface quality is dependent uponprocess parameters such as water jet pressure, feedrate, nozzle diameter, standoff distance and materialthickness during WJM of FRPs.In this process a focused stream of abrasiveparticles carried by high pressure water or air ata velocity of about 150 - 300 (m/sec) are made toimpinge on the work surface through a nozzleand the work material is removed by erosion bythe high velocity abrasive particles. The abrasiveparticles should have irregular shape and consistof sharp edges. The abrasive particles are directedonto the work piece through a nozzle [4].P. J. Singh, W. L. Chen, J. Munoz [7] experimentallystudied the effect of traverse speed, water jetpressure, abrasive flow rate and size, size of waterorifice and mixing tube on AWJ cut, surface finishfor different materials (aluminium, steel, glass andrubber). It was found that better surface finish isobtained at the top part of the cut surface of lowerwater jet pressure and by increasing abrasive flowrate decreasing traverse speed.Table I Characteristics of different variablesRamulu and Arola [8] conducted an experimentalinvestigation to study the effect of machiningparameters on the surface roughness (Ra) and kerftaper in AWJM of graphite/epoxy laminates. Taguchimethod (TM) and analysis of variance (ANOVA)indicated that grit size and standoff distance have themost significant influence on Ra. Abrasive flow rateand water jet pressures have the least influence on Raat any machining depth.M. A. Azmir, A.K. Ahsan, A. Rahmah, M.M. Noor,and A.A. Aziz [9] conducted an experiment on theoptimization of AWJM on Kevlar with multipleperformance characteristics using GRA. TheyOptimization of Abrasive Water Jet Machining Process Parameters Using Taguchi Grey Relational Analysis (TGRA)82

International Journal of Mechanical And Production Engineering, ISSN: 2320-2092,conclude that the performance characteristics of theAWJM process namely hydraulic pressure, abrasivemass flow rate, standoff distance and traverse rate areimproved together by using GRA.M. A. Azmir1, A.K. Ahsan, A. Rahmah hasperformed experimental analysis on AWJM to assessthe influence of surface roughness (Ra) and keft taperratio (TR) of aramid fiber reinforced composites usingTaguchi’s method and Analysis of Variance(ANOVA). They find traverse rate to have the mostsignificant effect on surface roughness (Ra) and kefttaper ratio (TR).I. Conner, M. Hasish, M. Ramulu investigated theAWJM of thin aerospace structural sheets ofgraphite/epoxy composites, INCOLEL, titanium andaluminium alloy. It was found that increasing thetraverse rate for a fixed water jet pressure, garnetabrasive size, and abrasive flow rate increases Ra.Bottom kerf width decreases with an increase intraverse speed. However, the rate of decreasebecomes less about increasing abrasive flow rate.M. Ramulu,P. Posinasetti, M. Hasish criticallyreviewed and evaluated the AWJ drilling modelsthrough the Mathematical modelling. It was foundthat the water pressure, abrasive flow rate and drillingtime significantly affected the dimensions andaccuracy of the drilled holes.Ersan Aslan, N. Camuscu, B. Birgoren haveoptimized cutting parameters (speed, feed, depth ofcut) on two performance measures-flank wear andsurface roughness in hard turning of steels withceramic tools. This was achieved by using Taguchitechniques. The combined effects were then studiedusing ANOVA.M.A. Azmir, A.K. Ahsan conducted experimentalinvestigation to study for surface roughness and kerfwidth of Kevlar machined by AWJM. They foundthat the type of abrasive being used has the mostsignificant on kerf width.Khan and Haque studied the effect of different typesof abrasive materials during AWJM. It was found thatgarnet abrasives produced the smallest kerf widthfollowed by aluminium oxide and silicon carbide.Silicon carbide produced the maximum kerf widthcompared to aluminium oxide and garnet due to itshigher hardness. It was also observed that the kerfwidth increases with the increase in water pressureand stand-off distance and decreases with the increaseof feed rate. The kerf taper was found to be higher ata higher standoff distance and feed rate, but smaller ata higher pressure.N. K. Jain, V. K. Jain, K. Deb carried outoptimization of AWJM process parameters (water jetVolume- 2, Issue-9, Sept.-2014pressure, nozzle diameter, traverse speed, mass flowrate of water and abrasive flow rate) using geneticalgorithm for material removal rate.M.Joseph Davidson, K. Balasubramanian, G. R. N.Tagore have predicted surface roughness of flowformed alloy by using design of experiments. Theeffects of the main parameters were studied and amathematical model developed on this basis.T. U. Siddiqui, M. Shukla used a hybrid Taguchi andresponse surface method approach for optimization ofsurface finish in AWJM of Kevlar composites. It wasfound that quality level and water jet pressure werethe most significant factors affecting Ra incomparison to abrasive flow rate.Siddiqui and Shukla presented simultaneousoptimization of multiple performance characteristicsnamely surface roughness and kerf taper in AWJcutting of aerospace grade Aramid composites usingthe Taguchi’s quality loss function. A considerableimprovement in performance characteristics isobtained at the optimized parameter settings ascompared to the initial settings.Yu Zhong presents a comprehensive study on thedepth of cut in AWJ cutting when a controlled nozzleoscillation technique and a multipass cuttingtechnique are jointly used with a view to increase thecutting performance. They find that multipass cuttingoperations can not only increase the total depth of cut,but also yield superior performance over the singlepass cutting.IV.TAGUCHI GREY RELATIONALANALYSIS (TGRA)Taguchi’s method is an efficient tool for the design ofhigh a quality manufacturing system; it is employedwhen the number of parameters is high. Dr. GenichiTaguchi, a Japanese engineer has developed a methodbased on orthogonal arrays (OA). In this methodquality is measured by the deviation of acharacteristic from its target value.A loss function is developed from this deviation.Uncontrollable factors which are also known as noisecause such deviation and result in loss. Taguchimethod seeks to minimize the noise since theelimination of noise factor is impractical and so aparameter called signal to noise ratio (S/N) is defined.To solve multiple performance characteristicproblems, the Taguchi method is coupled with GreyRelational Analysis (GRA). In GRA experimentaldata are first normalized in the range of zero to one.Grey relational coefficients are calculated to representthe correlation between the ideal and the actualnormalized data.Optimization of Abrasive Water Jet Machining Process Parameters Using Taguchi Grey Relational Analysis (TGRA)83

International Journal of Mechanical And Production Engineering, ISSN: 2320-2092,Volume- 2, Issue-9, Sept.-2014nearest OA fulfilling this condition is L27 (313). It canaccommodate a maximum three number of controlfactors, each at three levels with 27 experiments.All 27 experiments are conducted at 900 jetimpingement angle only. The specimen is weighedbefore and after the experimentation. The ratio of thevolume difference to total cutting time gives thevolumetric material removal rate.a)Checking and preparing the AWJ machineready for performing the machining operation.b)Performing cutting operation on specimensto ensure a lower kerf width and higher MRR.c)Calculating the weight of the specimenbefore and after machining, for the calculation ofMRR.d)Kerf width is calculated after experimentalfor every cut.VI.Fig.2 Flow chart of Taguchi’s method [6]V.CONTROLLABLE PARAMETERSThe possible controllable parameters of AWJM arewater jet orifice size, water jet pressure, abrasive gritsize, abrasive material, abrasive flow rate, traverserate, standoff distance, angle of attack, compositionof work piece.From the above a full factorial experimental setconsisting of abrasive flow rate, pressure and standoffdistance as process parameters considering each at 3levels with all possible combinations leading to atotal of 27 experiments is chosen. The processparameters range is specified in Table II.The equipment used for machining the samples isDWJ Flying Arm CNC abrasive water jet cuttingmachine equipped with KMT model of water jetpump with the designed pressure of 3800 bar(55000psi) and rated discharge of 2.3l/min. Themachine is equipped with a gravity feed type ofabrasive hopper, an abrasive feeder system, apneumatically controlled valve and a work table withdimension of 1600mm 2100mm. For the nozzleassembly, it has an orifice of 0.25mm diameter ofsapphire jewel. The abrasives were delivered usingcompressed air from a hopper to the mixing chamberand were regulated using a metering disc. All thecutting experiments were performed on INCONEL718 material and are single pass experimentsconducted by choosing standoff distance of 3mm andthe jet impact angle of 900. Granite sand abrasiveswere used as abrasives.Table II Range of process parametersParameters Symbol Level Level Level123Abrasive(A)2.72.853flow istance(mm)Selection of the particular orthogonal array from thestandard OA depends on the number of factors, levelsof each factor.Based on the above values and the required minimumnumber of experiments to be conducted (27), theEXPERIMENTATIONFig.3 Nozzle of AWJMThe kerf width was measured with the profileprojector of magnification x10 and a least count of0.02 mm. Kerf width of each cut was measured atthree different places for accurate evaluation and thespecimen is weighed before and after theexperimentation.Optimization of Abrasive Water Jet Machining Process Parameters Using Taguchi Grey Relational Analysis (TGRA)84

International Journal of Mechanical And Production Engineering, ISSN: 2320-2092,AbrasiveflowratePressureNozzle e6.78ue0.006355.330.930.0000.409Table V Response values for S/N 2753Main Effects Plot for SN ratiosData MeansAbrasive Flow RatePressureNozzle Tip Distance-2-3Mean of SN ratiosTable III Response for the input parametersS. AB C MRRKerfNo(mm3/min) width(mm)12.730 3 779.142.0422.730 4 8102.1432.730 5 825.422.1842.740 3 993.61.852.740 4 939.61.762.740 5 880.21.672.750 3 1053.21.5482.750 4 978.751.492.750 5 958.51.3610 2.85 30 3 808.132.111 2.85 30 4 770.892.1812 2.85 30 5 804.412.2413 2.85 40 3 955.81.814 2.85 40 4 955.81.8215 2.85 40 5 982.81.8416 2.85 50 3 1012.51.617 2.85 50 4 985.51.5818 2.85 50 5 985.51.5219 330 3 763.442.120 330 4 782.062.0521 330 5 782.062.0622 340 3 912.61.6223 340 4 977.41.824 340 5 9721.8225 350 3 924.751.4226 350 4 951.751.4627 350 5 924.751.4From table IX it can be seen that the highest value ofGRG is obtained in the 7th row, which is related tooptimal process parameters. The optimal parametersare abrasive flow rate 2.7lb/min, pressure 50kpsi, andstandoff distance 3mm. At these parameters weobserve optimum outputs as MRR 1053.2 mm3/minand kerf width 1.54mm.Volume- 2, Issue-9, to-noise: Larger is betterFig.3 Main Effects Plot for S/N ratiosVII.MINITABTable VI Comparison of S/N ratio valuesMINITAB is a powerful statistical software packageused in the areas of mathematics, statistics,economics, sports and engineering. It is highlyinteractive software which makes entering data,conducting regression analysis, ANOVA analysis,designing experiments using DOE, performingTaguchi analysis, drawing control charts forprocesses, performing reliability/survival tests,multivariate tests, plotting time series plots, etc. veryeasy and time saving. It is the best tool for data drivenquality improvement programs. In this project,MINITAB (version 17) has been used for ANOVAanalysis and for plotting various graphs.Table IV Analysis of Variance (ANOVA) for S/NratiosSourc DO AdjAdjFPeFSSMSValu ValA main effect plot is a plot of the mean responsevalues at each level of a design parameter or processvariable, this plot can be used to compare the relativestrength of the effects of the various factors. The signand magnitude of a main effect plot would giveinformation on the following: The sign of a main effect gives the directionof the effects starting average response valueincreases or decreases. The magnitude gives the strength of theeffect.From the above graphs, it can be seen that optimalconditions obtained from the graph are abrasive flowOptimization of Abrasive Water Jet Machining Process Parameters Using Taguchi Grey Relational Analysis (TGRA)85

International Journal of Mechanical And Production Engineering, ISSN: 2320-2092,rate 2.7lb/min, pressure 50kpsi and standoff distance3mm.Referring to table VII the S/N ratios for three levelscan be calculated using Grey Relational Grade basedon below formula.η 10 log(1/n)The individual optimum conditions are: abrasive flowrate level 1 (2.7lb/mm), pressure level 3 (50kpsi), andstandoff distance level 1 (3mm). Thus the overalloptimum conditions are A1-B3-C1 combination.Table VIII Optimum set of control factorsAbrasive FlowStandoffFactors/Lev Rate(A Pressure(Distance(els)B) (kpsi)C) (mm)(lb/min)2.750From table VI predicted S/N ratio is nearest to theconfirmation test S/N ratio; this explains that theobtained parameters are optimal.CONCLUSIONThe following conclusions can be drawn from theresults of the present work:yTable VII Summary of S/N ratiosFactorLevel 1 Level 2 Level 5.459distance(C)Optimumvalue The optimal parameter values are abrasive flowrate at 20.41 gm/sec, pressure at 344.7Mpa andstandoff distance at 3mm. At these parametersthe values of MRR and kerf width are 1053.2mm3/min and 1.54mm respectively. It is shown that the performance characteristicsof the AWJM process, namely water jetpressure, abrasive flow rate and standoffdistance are improved together by usingTaguchi Grey Relational Analysis. From ANOVA it is found that water jet pressurehas more significant effect on kerf width andMRR rather than abrasive flow rate and standoffdistance. The predicted S/N ratio is nearest to theconformation test S/N ratio; this explains thatthe TGRA process adopted for optimization ofparameters is accurate.REFERENCES[1]M. Hashish, “A modeling study of metal cutting withabrasive water jets”, ASME J. Eng. Mater. Tech. 106(1984) pp 88–100.[2]M. Hashish, “An investigation of milling with abrasivewaterjets”, ASME J. Eng. Ind. 111 (1989) 158–166.[3]J. John Rozario Jegaraj, N. Ramesh Babu, “A softcomputing approach for controlling the quality of cut withabrasive waterjet cutting system experiencing orifice andfocusing tube wear”, Journal of Materials ProcessingTechnology 185 (2007) pp 217–227.[4]S. Naveen & Aslam A. Hirani, “Design & Fabrication ofAbrasive Jet Machining”, International Journal ofMechanical and Production Engineering Research andDevelopment (IJMPERD) ISSN(P): 2249-6890; ISSN(E):2249-8001 (2014) pp.55-62[5]Koenig W., Wulf Ch., Grass P. and Willerscheid H.“Machining of fibre reinforced plastics”, Annals of CIRP,Vol. 34, No. 2, 1985.[6]Wei-Chung Weng, Fan Yang, Atef Z. Elsherbeni, “LinearAntenna Array Synthesis Using Taguchi’s Method: A NovelOptimization Technique in Electromagnetics”, IeeeTransactions On Antennas And Propagation, (2007) pp 723730.[7]Singh P.J., Chen W. L., Munoz J. “Comprehensiveevaluation of abrasive water jet cut surface quality”, inProceedings of the 6th American Water Jet Conference,Houston, USA, 1991.[8]Ramulu M., Arola D. “The influence of abrasive water jetcutting conditions on the surface quality of graphite/epoxy3VIII. VERIFICATIONThe predicted value for S/N ratio is obtained usingthe below formula.From table VIII the following calculations are done:ηVolume- 2, Issue-9, Sept.-2014 Y (A1 Y) (B3 Y) (C1 Y) A1 B3 C1 2Y [( 5.079) ( 2.625) ( 5.323)] [2 ( 5.865)]η -1.298 dBTherefore, the predicted average for optimumcondition is -1.298 dB.A confirmation test is performed with the obtainedoptimum cutting parameters (Abrasive flow rate2.7lb/min, pressure 50kpsi, Standoff distance 3mm).The values are taken for a single trial and the S/Nratio is calculated for this condition. The GRG 0.855 and S/N -1.362.Optimization of Abrasive Water Jet Machining Process Parameters Using Taguchi Grey Relational Analysis (TGRA)86

International Journal of Mechanical And Production Engineering, ISSN: 2320-2092,laminates”, International Journal of Machine Tools &Manufacture, Vol. 34, No. 3, 1994.[9]M. A. Azmir, A.K. Ahsan, A. Rahmah, M.M. Noor, andA.A. Aziz, “Optimization of Abrasive Waterjet MachiningProcess Parameters Using Orthogonal Array With GreyRelational Analysis”, Regional Conference on EngineeringMathematics, Mechanics, Manufacturing & Architecture(EM3ARC) (2007), pp 21 30.[10] M. A. Azmir1, A.K. Ahsan, A. Rahmah, “Investigation onAbrasive Waterjet Machining of Kevlar ReinforcedPhenolic Composite Using Taguchi Approach”, Proceedingsof the International Conference on Mechanical Engineering2007 (ICME2007) (2007), pp 29-31.[11] Conner I., Hashish M., Ramulu M. “Abrasive water jetmachining of aerospace structural sheet and thin platematerials”, in Proceedings of the 12th American Water jetConference, Houston, USA, 2003.[12] Ramulu M., Posinasetti P. and Hashish M. “Analysis ofabrasive water jet drilling process”, WJTA American Waterjet Conference, Houston, Texas, 2005.[13] Ersan Aslan, N.Camuscu, B.Birgoren “Optimization ofcutting parameters on to performance measures”-flank wearand surface roughness, Material and Design, vol 28,issue5,Elsevier, 2007.[14] Azmir M.A. and Ahsan A.K, “Investigation on glass/epoxycomposite surfaces machined by abrasive water jetmachining”, Journal of Materials Processing Technology,2007.Volume- 2, Issue-9, Sept.-2014[15] Khan A.A. and Haque M.M. “Performance of differentabrasive materials during abrasive water jet machining ofglass”, Journal of Materials Processing Technology, Vol.191, 2007.[16]

Abstract- Abrasive Water Jet Machining (AWJM) is a versatile machining process primarily used to machine hard and difficult to machine materials. The objective of this paper is to optimize material removal rate and kerf width simultaneously using AWJM process on INCONEL 718. The process parameters are chosen as abrasive flow rate, pressure, and standoff distance. Taguchi Grey Relational .

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