OPTIMIZATION OF MATERIAL REMOVAL RATE AND SURFACE ROUGHNESSIN WED-MACHINING OF TiNi SMA USING GREY RELATION ANALYSIS
|
|
- Hugh Shanon Marshall
- 5 years ago
- Views:
Transcription
1 OPTIMIZATION OF MATERIAL REMOVAL RATE AND SURFACE ROUGHNESSIN WED-MACHINING OF TiNi SMA USING GREY RELATION ANALYSIS Manjaiah M 1*, Narendranath S 2, Basavarajappa S 3 1* Dept. of Mechanical Engineering, NITK, Surathkal, , manjaiahgalpuji@gmail.com 2 Dept. of Mechanical Engineering, NITK, Surathkal, , snnath88@yahoo.co.in 3 Dept. of Mechanical Engineering, UBDT college of Engg., Davangere, , basavarajappas@yahoo.com Abstract In the present paper, wire electro discharge machining (WEDM) of TiNi shape memory alloy (SMA) is studied. Influence of pulse on time, pulse off time, servo voltage, dielectric fluid pressure and wire speed are investigated for material removal rate (MRR) and surface roughness (Ra) during machining of a stepped TiNi beam. To optimize the MRR and Ra simultaneously, grey relational analysis (GRA) is employed with Taguchi L 27 orthogonal array. Through GRA, grey relation grade is used as performance index to find the optimal process parameters for the machining characteristics (MRR and Ra). Analysis of variance (ANOVA) shows that the pulse on time is the most significant parameter affecting the MRR and Ra. Confirmation results proves the potential of GRA to optimize the multi machining characteristics of WEDM process parameters. Keywords:WEDM,TiNi SMA, MRR, Ra, Multi optimization, GRA, L 27 Orthogonal array 1. Introduction TiNi shape memory alloy (SMA) is an important class of material, used in various fields such as medical, micro engineering and commercial sectors due to excellent wear, outstanding corrosion resistance and biocompatibility properties. Furthermore, SMA has often been classified into difficult-to-machine material due to low thermal conductivity, which in turn hinders quick dissipation of heat caused by machining and thus leading to higher tool wear and severe strain hardening (Weinertand Petzoldt 2004, Lin et al., 2000). Hence, due to difficulty in conventional machining of TiNi SMA, the non-traditional machining is usually performed using special machining techniques such as electric discharge machining (EDM) (Alidoosti et al., 2013) and wire electric discharge machining (WEDM) (Hsieh et al., 2009). It is a thermo electric process; material removal takes place by the discrete sparks discharge between the electrode and workpiece. The electric sparks melt and vaporizes some amount of material from the workpiece, which is flushed away from the workpiece surface by the dielectric pressure. The selection of optimum machining parameter combination to obtain higher material removal rate (MRR) and better surface roughness (Ra) is a difficult task in WEDM because of numerous input process parameters and stochastic process. Hence in the present study Taguchi method and grey relation approach is used optimize simultaneously the responses of MRR and Ra of WEDM of TiNi SMA. 2. Experimental setup and design In the present work, five parameters, namely, pulse on time, pulse of time, servo voltage, flushing pressure and wire speed were identified and the range of the each parameter was determined from the preliminary experiments. Each process parameter was investigated at three levels to study the non-linearity effect of the parameters. The brass wire (Ø0.25mm) was used as electrode, which consists of 65% zinc and 35% copper. Fixed parameters such as peak current of 14A, short pulse time of 0.2µs and wire tension is of 1daN. The experiments were performed on Robofill -290 WEDM (Make: Charmills Co.) as per L 27 orthogonal array (Ross, 1996), the identified controllable parameters in WEDM of TiNi SMA experiments and their associated levels and the experimental layout plan is shown in Table 1. Based on the experimental layout shown in Table 1, the experiments were performed. The machining characteristics material removal rate (MRR) and surface roughness (Ra) were measured. MRR was calculated by the volume of material removed with respect to time and Ra was measured in a Mitutoyo surface roughness tester. The mean values and S/N ratios are depicted in Table
2 OPTIMIZATION OF MATERIAL REMOVAL RATE AND SURFACE ROUGHNESSIN WED-MACHINING OF TiNi SMA USING GREY RELATION ANALYSIS Sl. No. Pulse on time (µs)a Pulse off time (µs)b Table 1: Experimental plan with the responses and corresponding S/N ratios Servo voltage (V) C Flushing pressure (bar) D Wire speed (m/min) E MRR (mm 3 /min) S/N ratio (MRR) Surface Roughness (µm) S/N ratio (Ra) Results and discussion 3.1 Analysis of variance for MRR Table: 2 ANOVA for MRR based on S/N ratio Parameter DOF SS MS % contribution A B C D E Error Total % confidence level, DOF- Degrees of freedom, SS- Sum of squares, MS- Mean square The analysis of variance (ANOVA) depicts the relative significance of each individual process parameter and their corresponding percentage of contribution towards the response. ANOVA is performed using S/N ratios and to obtain the percentage contribution of each individual process parameter. It is found that from Table 2 Pulse on time (A) has a most significant influence and it can be seen that the contribution is 81.90% on the MRR and pulse off time, servo reference voltage and wire speed has less significant on MRR. The wire speed has no effect on the MRR. Higher the pulse on time higher will be the MRR due to increased discharge energy, longer time to melt and intensity of spark. 3.2 Analysis of variance for Surface roughness Table: 3 ANOVA for MRR based on S/N ratio Parameter DOF SS MS % Contribution A B C D E
3 Error Total % confidence level, DOF- Degrees of freedom, SS- Sum of squares, MS- Mean square Analysis of variance for surface roughness justifies the goodness of fit. The results of ANOVA for Ra are presented in the Table 3. ANOVA calculated for 95% of confidence level. The aim is study the which are the significant machining parameters affecting the surface roughness or not. From the Table 3 it analyzed that pulse on time have greater influence on surface roughness and also it shows that pulse off time, servo voltage and flushing pressure affecting the surface roughness. 3.3 Multi response optimization using grey relation Grey relation data processing is performed by using S/N ratio of experimental data. In this study, a linear normalization of the S/N ratios for MRR and Ra were performed. A linear data pre-processing method for the S/N ratio can be expressed by following relation as found in (1) below: ( )= ( ) ( ) ( ) ( ) (1) Where y i * (k) is the sequence after the data processing; ( ) is original sequence of S/N ratio, i = 1,2,3,...,m and k = 1,2,3,...,n with m = 27 and n = 2; max ( ) is the largest value of ( ); min ( ) is the smallest value of ( ). The outcomes are represented as ( ) and ( )for reference sequence and comparability sequence, respectively. Basically, the larger normalized S/N ratio corresponds to the better performance and the best-normalized S/N ratio is equal to unity. Followed by data processing, it is necessary to establish the relationship on ideal versus actual normalized values. It is calculated by calculating the grey relational coefficient, which is expressed in the equation (2) [6]. ( ). ( ) =. ( ). 0 ( ). ( ) (2) Where ( ) is the deviation sequence of reference sequence ( ) and comparability sequence ( ) i.e. ( ) = ( ) ( ) is the absolute value of the difference between ( )and ( ), = max. max. ( ), is the distinguishing coefficients 0,1. is set as 0.5 in this study. The purpose of defining this coefficient is to show the relational degree between the reference sequences ( ) and comparability of 27 sequences ( ), where i = 1, 2, 3... m and k = 1, 2, 3,..., n with m = 27 and n = 2 in this study. Using data processing values the deviation sequence can be calculated as follows (Jangra et al., 2010), (1) = = (2) = = Then, = ( , ). = (1) = (2)= = (1) = (2)= According to deviation sequence and equation (2), the grey relational coefficient ( ). ( ) are calculated as follows:... (1). (1) =... = (2). (2) =... = The grey relational grade is a weighting-sum of the grey relational coefficients. The overall evaluation of multiple performance characteristics is based on the grey relational grade and it is defined as follows, (. )= ( ). ( ) (3) Where represents the weighting value of the k th performance characteristics, and = 1. Using the same weighing values of MRR and Ra as were assigned in utility analysis (i.e. w 1 = w 2 = 0.5), the grey relational grade are calculated. Table 4 lists down the response table for grey relation coefficients and grey relation grade corresponding to machining parameters. = min. min. ( ), 351-3
4 OPTIMIZATION OF MATERIAL REMOVAL RATE AND SURFACE ROUGHNESSIN WED-MACHINING OF TiNi SMA USING GREY RELATION ANALYSIS Table: 4 Response table for grey relation coefficients and grade Grey Relational Co-efficient Grey Sl. No. relation MRR Ra grade Fig. 1 Graph of gray relation grade According to performed experiment design, it is clearly observed from Table 4 and Fig. 1 that the WED-machining parameters setting of experiment no. 26 has the highest grey relation grade. Thus, the 26 th trial of experiment gives the best multiperformance characteristics among the 27 experiments. 3.4 Optimal level of process parameters Calculation of grey relation reasoning grade is carried out to obtain optimum parameters for obtaining higher MRR and lower surface roughness. Optimization of the multiple performance characteristics can be converted into optimization of single grey relational grade. It is clearly observed from Table 3 for grey relational grade, the process parameters setting of trial 26 has the highest grey relational grade. A 3 B 3 C 2 D 1 E 2 combination shows higher grey relational grade value hence as per GRA these combination of parameters gives the optimal process parameter setting. This may be considered as an optimal combination of WEDM process parameters so as to produce desired values of the performance characteristics. Therefore, A 3 (1µs), B 3 (25µs), C 2 (40V), D 1 (1.8 kg/cm 2 ) and E 2 (8N) is the optimal parameter combination for multi-quality characteristics. Fig. 2 Response graph for each level of the WEDmachining parameters
5 During the machining in WEDM process, the value of grey relational grade for each operating parameter concerning the MRR and surface roughness is the greater the better. Fig. 2 shows the response graph of the total mean of the grey relational grade. The highest steep slope of response graph indicates the more influencing operating parameter in the multi response performance characteristic. The front four operating factors namely pulse on time (A), pulse off time (B), servo voltage (c) and Flushing pressure (D) have highest significance on the output responses. From the analysis of variance it is analysed that pulse on time, pulse off time and servo voltage having noticeable resources of influential parameters on the improvable quality characteristics. The other parameters are considered as unnoticeable effect on the output responses. Based on the above discussion, the optimum cutting parameter levels of A 3 B 3 C 2 D 1 E 2 for both the performance characteristics of MRR and surface roughness simultaneously. 4. Conclusions In the present work, wire electro discharge machining characteristics of TiNi SMA has been studied. Taguchi based grey relation analysis is used to optimize the MRR and surface roughness (Ra), simultaneously. Based on the experimental analysis the following conclusions are made. 1. From the analysis of variance (ANOVA) the process parameters pulse on time, pulse off time, and servo voltage are the major influencing parameters on the MRR and surface roughness. 2. Pulse on time is the major influencing parameter for both the responses MRR and surface roughness. Increase in pulse on time and servo voltage increased MRR and surface roughness was achieved. 3. Grey relational analysis was used to determine the optimal combination of process parameters for multiple machining characteristics (MRR and Ra). Equal weights were assigned to both the machining characteristics in calculating the grey relational grade. The A 3 B 3 C 2 D 1 E 2 combination ofparameters level provides an optimal machining characteristic. References Weinert K, PetzoldtV(2004), Machining of NiTi based shape memory alloys. Materials Science Engineering A, 378: Lin HC, Lin KM, Chen YC. A (2000), study on the machining characteristics of Ti 50 Ni 50 shape memory alloys.journal of Materials Processing Technology,Vol 105, pp Alidoosti, Ghafari-Nazari A, Moztarzadeh F, Jalali N, Moztarzadeh S, Mozafari M (2013) Electrical discharge machining characteristics of nickel-titanium shape memory alloy based on full factorial design. Journal of Intelligent Material Systems and Structures, Vol, pp1 11. Hsieh SF, Chen SL, Lin HC, Lin MH, Chiou SY (2009), The machining characteristics and shape recovery ability of Ti Ni X (X=Zr, Cr) ternary shape memory alloys using the wire electro-discharge machining. International Journal of Machine Tools and Manufacture,Vol49, pp Ross PJ (1996), Taguchi Techniques for Quality Engineering, McGraw-Hill, New York. Jangra K, Jain A, Grover S (2010), Optimization of multiple-machining characteristics in wire electrical discharge machining of punching die using Grey relational analysis.industrial Research, Vol 69,pp
Parameter Optimization of EDM on En36 Alloy Steel For MRR and EWR Using Taguchi Method
IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) e-issn: 2278-184,p-ISSN: 2320-334X, Volume 13, Issue 3 Ver. VII (May- Jun. 201), PP 5-5 www.iosrjournals.org Parameter Optimization of EDM on
More informationAPPLICATION OF GREY RELATIONAL ANALYSIS TO MACHINING PARAMETERS DETERMINATION OF WIRE ELECTRICAL DISCHARGE MACHINING
APPLICATION OF GREY RELATIONAL ANALYSIS TO MACHINING PARAMETERS DETERMINATION OF WIRE ELECTRICAL DISCHARGE MACHINING J.T. Huang 1 and Y.S. Liao 1 Department of Automatic Engineering, Kaoyuan Institute
More informationModeling of Wire Electrical Discharge Machining Parameters Using Titanium Alloy (Ti-6AL-4V)
Modeling of Wire Electrical Discharge Machining Parameters Using Titanium Alloy (Ti-6AL-4V) Basil Kuriachen 1, Dr. Josephkunju Paul 2, Dr.Jose Mathew 3 1 Research Scholar, Department of Mechanical Engineering,
More informationA Parametric Optimization of Electric Discharge Drill Machine Using Taguchi Approach
A Parametric Optimization of Electric Discharge Drill Machine Using Taguchi Approach Samar Singh, Lecturer, Dept of Mechanical Engineering, R.P. Indraprastha Institute of Technology (Karnal) MukeshVerma,
More informationInternational Journal of Scientific & Engineering Research, Volume 5, Issue 1, January ISSN
International Journal of Scientific & Engineering Research, Volume 5, Issue 1, January-2014 2026 Modelling of Process Parameters on D2 Steel using Wire Electrical Discharge Machining with combined approach
More informationOptimization of WEDM Parameters for Super Ni-718 using Neutrosophic Sets and TOPSIS Method
Optimization of WEDM Parameters for Super Ni-718 using Neutrosophic Sets and TOPSIS Method Y Rameswara Reddy 1*, B Chandra Mohan Reddy 2 1,2 Department of Mechanical Engineering, Jawaharlal Nehru Technological
More informationOptimization of Machining Parameters in Wire Cut EDM of Stainless Steel 304 Using Taguchi Techniques
Advanced Materials Manufacturing & Characterization Vol. 8 Issue 1 (018) Advanced Materials Manufacturing & Characterization journal home page: www.ijammc-griet.com Optimization of Machining Parameters
More informationModeling and Optimization of WEDM Process Parameters on Machining of AISI D2 steel using Response Surface Methodology (RSM)
Modeling and Optimization of WEDM Process Parameters on Machining of AISI D2 steel using Response Surface Methodology (RSM) Sk. Mohammed Khaja 1, Ratan Kumar 2 Vikram Singh 3 1,2 CIPET- Hajipur, skmdkhaja@gmail.com
More informationOptimization of MRR and SR by employing Taguchis and ANOVA method in EDM
Optimization of and SR by employing Taguchis and ANOVA method in EDM Amardeep Kumar 1, Avnish Kumar Panigrahi 2 1M.Tech, Research Scholar, Department of Mechanical Engineering, G D Rungta College of Engineering
More informationOptimization of machining parameters of Wire-EDM based on Grey relational and statistical analyses
int. j. prod. res., 2003, vol. 41, no. 8, 1707 1720 Optimization of machining parameters of Wire-EDM based on Grey relational and statistical analyses J. T. HUANG{* and Y. S. LIAO{ Grey relational analyses
More informationStatistical and regression analysis of Material Removal Rate for wire cut Electro Discharge Machining of SS 304L using design of experiments
Vol. 2(5), 200, 02028 Statistical and regression analysis of Material Removal Rate for wire cut Electro Discharge Machining of SS 304L using design of experiments Vishal Parashar a*, A.Rehman b, J.L.Bhagoria
More informationOptimization of Cutting Parameter of (SS302) on EDM using Taguchi Method Chintan A. Prajapati 1 Prof. Dr. Prashant Sharma 2 Prof.
IJSRD - International Journal for Scientific Research & Development Vol. 2, Issue 01, 14 ISSN (online): 2321-013 Optimization of tting Parameter of (SS302) on EDM using Taguchi Method Chintan A. Prajapati
More informationExperimental Investigation of Micro-EDM Process on Brass using Taguchi Technique
Experimental Investigation of Micro-EDM Process on Brass using Taguchi Technique Ananya Upadhyay ananya.upadhyay@gmail.com Vijay Pandey Vinay Sharma Ved Prakash CSIR- Central Mechanical Engineering Research
More informationOptimization of EDM process parameters using Response Surface Methodology for AISI D3 Steel
Optimization of EDM process parameters using Response Surface Methodology for AISI D3 Steel Mr.B.Gangadhar 1, Mr.N. Mahesh Kumar 2 1 Department of Mechanical Engineering, Sri Venkateswara College of Engineering
More informationEffect and Optimization of EDM Process Parameters on Surface Roughness for En41 Steel
, pp. 33-358 http://dx.doi.org/10.157/ijhit.01.9.5.9 Effect and Optimization of EDM Process Parameters on Surface Roughness for En1 Steel Ch. Maheswara Rao 1 and K.Venkatasubbaiah 1 (Assistant Professor,
More informationStudy of EDM Parameters on Mild Steel Using Brass Electrode
Study of EDM Parameters on Mild Steel Using Brass Electrode Amit Kumar #1, Abhishek Gaikwad *2, Amit Tiwari #3 # 1,3, Production Engineering (ME), SSET, Allahabad-211007, SHIATS, Allahabad, Uttar Pradesh
More informationAnalysisoMRRandSRwithDifferentElectrodeforSS316onDi-SinkingEDMusingTaguchiTechnique
Global Journal of Researches in Engineering Mechanical and Mechanics Engineering Volume 13 Issue 3 Version 1.0 Year 013 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global
More informationPuttur, Andhra Pradesh, India , Andhra Pradesh, India ,
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
More informationStudy of water assisted dry wire-cut electrical discharge machining
Indian Journal of Engineering & Materials Sciences Vol. 1, February 014, pp. 75-8 Study of water assisted dry wire-cut electrical discharge machining S Boopathi* & K Sivakumar Department of Mechanical
More informationImpact of Microchannel Geometrical Parameters in W-EDM Using RSM
International Journal of Bioinformatics and Biomedical Engineering Vol. 1, No. 2, 2015, pp. 137-142 http://www.aiscience.org/journal/ijbbe Impact of Microchannel Geometrical Parameters in W-EDM Using RSM
More informationEXPERIMENTAL INVESTIGATIONS ON ORBITAL ELECTRO DISCHARGE MACHINING OF INCONEL 718 USING TAGUCHI TECHNIQUE
International Journal of Modern Manufacturing Technologies ISSN 2067 3604, Vol. IV, No. 1 / 2012 53 EXPERIMENTAL INVESTIGATIONS ON ORBITAL ELECTRO DISCHARGE MACHINING OF INCONEL 718 USING TAGUCHI TECHNIQUE
More informationParametric Study and Optimization of WEDM Parameters for Titanium diboride TiB2
Parametric Study and Optimization of WEDM Parameters for Titanium diboride TiB2 Pravin R. Kubade 1, Sunil S. Jamadade 2, Rahul C. Bhedasgaonkar 3, Rabiya Attar 4, Naval Solapure 5, Ulka Vanarase 6, Sayali
More informationAn investigation of material removal rate and kerf on WEDM through grey relational analysis
Journal of Mechanical Engineering and Sciences ISSN (Print): 2289-4659; e-issn: 2231-8380 Volume 12, Issue 2, pp. 3633-3644, June 2018 Universiti Malaysia Pahang, Malaysia DOI: https://doi.org/10.15282/jmes.12.2.2018.10.0322
More informationModeling of Wire Electrical Discharge Machining of AISI D3 Steel using Response Surface Methodology
5 th International & 26 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 214) December 12 th 14 th, 214, IIT Guwahati, Assam, India Modeling of Wire Electrical Discharge Machining
More informationExperimental study of electrical discharge drilling of stainless steel UNS S30400
IOP Conference Series: Materials Science and Engineering PAPER OPEN ACCESS Experimental study of electrical discharge drilling of stainless steel UNS S30400 To cite this article: E A H Hanash and M Y Ali
More informationPost Graduate Scholar, Department of Mechanical Engineering, Jalpaiguri Govt. Engineering College, India. 2
International Journal of Technical Research and Applications e-issn: 30-8163, www.ijtra.com Volume 3, Issue 3 (May-June 015), PP. 5-60 INFLUENCE OF CONTROL PARAMETERS ON IN ELECTRICAL DISCHARGE MACHINING
More informationTaguchi-grey relational based multi response optimization of electrical process parameters in electrical discharge machining
Indian Journal of Engineering & Materials Science Vol. 20, December 2013, pp. 471-475 Taguchi-grey relational based multi response optimization of electrical process parameters in electrical discharge
More informationModelling And Optimization Of Electro Discharge Machining In C45 Material
IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) e-issn: 2278-1684,p-ISSN: 2320-334X PP. 25-32 www.iosrjournals.org Modelling And Optimization Of Electro Discharge Machining In C45 Material
More informationOptimization of Wire EDM Process Parameters of Al 6061/Al 2 O 3 /3%red mud MMC
Optimization of Wire EDM Process Parameters of Al 6061/Al 2 O 3 /3%red mud MMC Dhinesh kumar.k #1 Sivakumar.M *2, Sivakumar.K *3,Kumar.M *4 # P.G scholar, Department of Mechanical Engineering,Bannari Amman
More informationEXPERIMENTAL INVESTIGATION OF MRR, SURFACE ROUGHNESS AND OVERCUT OF AISI 304 STAINLESS STEEL IN EDM A THESIS SUBMITTED IN PARTIAL FULFILMENT
EXPERIMENTAL INVESTIGATION OF MRR, SURFACE ROUGHNESS AND OVERCUT OF AISI 304 STAINLESS STEEL IN EDM A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF Bachelor of Technology
More informationNumerical Modeling and Multi-Objective Optimization of Micro-Wire EDM Process
5 th International & 26 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12 th 14 th, 2014, IIT Guwahati, Assam, India Numerical Modeling and Multi-Objective
More informationS. S.Mahapatra National Institute of Technology Department of Mechanical Engineering Rourkela. INDIA. Amar Patnaik.
S. S.Mahapatra and Amar Patnaik S. S.Mahapatra ssm@nitrkl.ac.in National Institute of Technology Department of Mechanical Engineering Rourkela. INDIA Amar Patnaik amar_mech@sify.com G.I.E.T Department
More informationAssociate Professor, Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, India
Optimization of machine process parameters on material removal rate in EDM for EN19 material using RSM Shashikant 1, Apurba Kumar Roy 2, Kaushik Kumar 2 1 Research Scholar, Department of Mechanical Engineering,
More informationInternational Journal of Scientific & Engineering Research, Volume 5, Issue 12, December ISSN IJSER
International Journal of Scientific & Engineering Research, Volume 5, Issue 12, December-2014 29 Prediction of EDM process parameters by using Artificial Neural Network (ANN) - A Prediction Technique Mitali
More informationInvestigation of effect of process parameters in micro hole drilling
Investigation of effect of process parameters in micro hole drilling Vaibhav Gosavi, Dr. Nitin Phafat, Dr. Sudhir Deshmukh 3 Research scholar,me MFG, JNEC Asso. Prof. Mech. Dept., JNEC 3 Principal, JNEC
More informationStudy of the effect of machining parameters on material removal rate and electrode wear during Electric Discharge Machining of mild steel
Journal of Engineering Science and Technology Review 5 (1) (2012) 14-18 Research Article JOURNAL OF Engineering Science and Technology Review www.jestr.org Study of the effect of machining parameters on
More informationMODELING OF SURFACE ROUGHNESS IN WIRE ELECTRICAL DISCHARGE MACHINING USING ARTIFICIAL NEURAL NETWORKS
Int. J. Mech. Eng. & Rob. Res. 013 P Vijaya Bhaskara Reddy et al., 013 Research Paper ISSN 78 0149 www.ijmerr.com Vol., No. 1, January 013 013 IJMERR. All Rights Reserved MODELING OF SURFACE ROUGHNESS
More informationPercentage of harmful discharges for surface current density monitoring in electrical discharge machining process
1677 Percentage of harmful discharges for surface current density monitoring in electrical discharge machining process O Blatnik*, J Valentincic, and M Junkar Faculty of Mechanical Engineering, University
More informationRESPONSE SURFACE ANALYSIS OF EDMED SURFACES OF AISI D2 STEEL
Advanced Materials Research Vols. 264-265 (2011) pp 1960-1965 Online available since 2011/Jun/30 at www.scientific.net (2011) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/amr.264-265.1960
More informationCHAPTER -6 ANALYSIS AND DISCUSSION OF RESULTS
CHAPTER -6 ANALYSIS AND DISCUSSION OF RESULTS This chapter presents the analysis and discussion of the results obtained from the experimental work conducted in Chapter-5. The effect of cryogenic treated
More informationOptimization of Machining Parameters in ECM of Al/B4C Composites Using Taguchi Method
International Journal of Applied Science and Engineering 2014. 12, 2: 87-97 Optimization of Machining Parameters in ECM of Al/B4C Composites Using Taguchi Method S. R. Rao a* and G. Padmanabhan b a Department
More informationA study to achieve a fine surface finish in Wire-EDM
Journal of Materials Processing Technology 149 (24) 165 171 A study to achieve a fine surface finish in Wire-EDM Y.S. Liao a,, J.T. Huang b, Y.H. Chen a a Department of Mechanical Engineering, National
More informationOptimization of process parameter in electrochemical machining. Of Inconel 718 by Taguchi analysis
International Journal of Engineering Research and General Science Volume, Issue, January-February, 05 ISSN 09-70 Optimization of process parameter in electrochemical machining Of Inconel 78 by Taguchi
More informationELECTRIC DISCHARGE MACHINING AND MATHEMATICAL MODELING OF Al-ALLOY-20 % SiC p COMPOSITES USING COPPER ELECTRODE
International Journal of Mechanical and Production Engineering Research and Development (IJMPERD ) ISSN 2249-6890 Vol.2, Issue 2 June 2012 37-46 TJPRC Pvt. Ltd., ELECTRIC DISCHARGE MACHINING AND MATHEMATICAL
More informationMr. Harshit K. Dave 1, Dr. Keyur P. Desai 2, Dr. Harit K. Raval 3
Investigations on Prediction of MRR and Surface Roughness on Electro Discharge Machine Using Regression Analysis and Artificial Neural Network Programming Mr. Harshit K. Dave 1, Dr. Keyur P. Desai 2, Dr.
More informationPerformance Evolution and Selection of Controllable Process variables in ECM for Al, B4C Metal Matrix Composites
International Journal of Management, IT & Engineering Vol. 8 Issue 12, December 2018, ISSN: 2249-0558 Impact Factor: 7.119 Journal Homepage: Double-Blind Peer Reviewed Refereed Open Access International
More informationStudy on Erosion Mechanism of Magnetic-field-assisted Micro-EDM
Study on Erosion Mechanism of Magnetic-field-assisted Micro-EDM Xuyang Chu a, Kai Zhu b, Yiru Zhang c and Chunmei Wang d Department of mechanical and electrical engineering, Xiamen University, Xiamen 361005,
More informationOptimization 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
More informationAll about sparks in EDM
All about sparks in EDM (and links with the CLIC DC spark test) Antoine Descoeudres, Christoph Hollenstein, Georg Wälder, René Demellayer and Roberto Perez Centre de Recherches en Physique des Plasmas
More informationMATHEMATICAL MODELING OF MATERIAL REMOVAL RATE OF T90Mn2W50Cr45 TOOL STEEL IN WIRE ELECTRICAL DISCHARGE MACHINE
International Journal of Mechanical and Materials Engineering (IJMME), Vol. 7 (01), No. 3, 03-08. MATHEMATICAL MODELING OF MATERIAL REMOVAL RATE OF T90MnW50Cr45 TOOL STEEL IN WIRE ELECTRICAL DISCHARGE
More informationDecision Science Letters
Decision Science Letters 4 (2015) 211 226 Contents lists available at GrowingScience Decision Science Letters homepage: www.growingscience.com/dsl Parameter selection in non-traditional machining processes
More informationVOL. 11, NO. 2, JANUARY 2016 ISSN
MULTIPLE-PERFORMANCE OPTIMIZATION OF DRILLING PARAMETERS AND TOOL GEOMETRIES IN DRILLING GFRP COMPOSITE STACKS USING TAGUCHI AND GREY RELATIONAL ANALYSIS (GRA) METHOD Gallih Bagus W. 1, Bobby O. P. Soepangkat
More informationCOMPANY : ELECTRONICA MACHINE TOOLS, PUNE, INDIA
Taguchi Method Case-Study OPTIMIZATION of ELECTRIC DISCHARGE MACHINE (EDM) by Dr. P. R. Apte IIT Bombay, INDIA 8. IDENTIFY THE MAIN FUNCTION, 2. IDENTIFY THE NOISE FACTORS, TESTING CONDITIONS, AND QUALITY
More informationStatistical and Experimental Study on the Influence of Input Parameters on the Dimensional Accuracy of Workpiece in EDM
Proceedings of the 212 International Conference on Industrial Engineering and Operations Management Istanbul, Turkey, July 3 6, 212 Statistical and Experimental Study on the Influence of Input Parameters
More informationExperimental Investigation of Machining Parameter in Electrochemical Machining
Experimental Investigation of Machining Parameter in Electrochemical Machining Deepanshu Shrivastava 1, Abhinav Sharma 2, Harsh Pandey 2 1 M.TECH Sholar, DR.C.V. RAMAN UNIVERSITY, KOTA C.G.,INDIA 2 M.TECH
More informationMULTIPHYSICS BASED ELECTRICAL DISCHARGE MODELING
MULTIPHYSICS BASED ELECTRICAL DISCHARGE MODELING Abhishek Mishra MSD,BARC Dr. D.Datta HPD,BARC S.Bhattacharya RRDPD,BARC Dr. G.K Dey MSD,BARC Santosh Kr. MSD,BARC ELECTRIC DISCHARGE MACHINING o Electric
More informationPerformance analysis of µed-milling process using various statistical techniques
Int. J. Machining and Machinability of Materials, Vol. 11, No. 2, 2012 183 Performance analysis of µed-milling process using various statistical techniques G. Karthikeyan Department of Mechanical Engineering,
More informationADVANCES in NATURAL and APPLIED SCIENCES
ADVANCES in NATURAL and APPLIED SCIENCES ISSN: 1995-0772 Published BYAENSI Publication EISSN: 1998-1090 http://www.aensiweb.com/anas 2017 April 11(4): pages 260-269 Open Access Journal A Study On Wet And
More informationTAGUCHI ANOVA ANALYSIS
CHAPTER 10 TAGUCHI ANOVA ANALYSIS Studies by varying the fin Material, Size of Perforation and Heat Input using Taguchi ANOVA Analysis 10.1 Introduction The data used in this Taguchi analysis were obtained
More informationInfluence of Electrode Material and Process Parameters on Surface Quality and MRR in EDM of AISI H13 using ANN
Influence of Electrode Material and Process Parameters on Surface Quality and MRR in EDM of AISI H13 using ANN Bhavesh A. Patel 1, D. S. Patel 2, Haresh A. Patel 3 1 (Assistant Professor, Department of
More informationModeling and Simulation of Surface Roughness in Wire Electrical Discharge Turning Process
nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 7) Modeling and Simulation of Surface Roughness in Wire Electrical Discharge Turning Process Xiaoteng
More informationInfluence of Input Parameters on Characteristics of Electro Chemical Machining Process
International Journal of Applied Science and Engineering 23., : 3-24 Influence of Input Parameters on Characteristics of Electro Chemical Machining Process C. Senthilkumara,*, G. Ganesana, and R. Karthikeyanb
More informationParameters Optimization of Rotary Ultrasonic Machining of Glass Lens for Surface Roughness Using Statistical Taguchi s Experimental Design
Parameters Optimization of Rotary Ultrasonic Machining of Glass Lens for Surface Roughness Using Statistical Taguchi s Experimental Design MUHAMMAD HISYAM LEE Universiti Teknologi Malaysia Department of
More informationDrilling Microholes in Hot Tool Steel by Using Micro-Electro Discharge Machining
Materials Transactions, Vol. 48, No. 2 (27) pp. 25 to 21 #27 The Japan Institute of Metals Drilling Microholes in Hot Tool Steel by Using Micro-Electro Discharge Machining T. Y. Tai 1, T. Masusawa 2 and
More informationAlgorithm for Modeling Wire Cut Electrical Discharge Machine Parameters using Artificial Neural Network
Algorithm for Modeling Wire Cut Electrical Discharge Machine Parameters using Artificial Neural Network G.Sankara Narayanan #1, D.Vasudevan #2 # Department of Mechanical Engineering, #1 SBM College of
More informationMODELING AND OPTIMIZATION FOR DRILLING OF HIGH ASPECT RATIO BLIND MICRO HOLES IN MICRO EDM
MODELING AND OPTIMIZATION FOR DRILLING OF HIGH ASPECT RATIO BLIND MICRO HOLES IN MICRO EDM Swapan Barman 1*, Kousv Mondol 2, Nagahanumaiah 3, Asit Baran Puri 4 1* CSIR-Central Mechanical Engineering Research
More information*Corresponding author: Received November 06, 2013; Revised November 20, 2013; Accepted November 29, 2013
American Journal of Mechanical Engineering, 013, Vol. 1, No. 6, 155-160 Available online at http://pubs.sciepub.com/ajme/1/6/ Science and Education Publishing DOI:10.1691/ajme-1-6- Development of RSM Model
More informationMaterial removal characteristics of microslot (kerf) geometry
DOI 10.1007/s00170-010-2645-z ORIGINAL ARTICLE Material removal characteristics of microslot (kerf) geometry in μ-wedm on aluminum Kodalagara Puttanarasaiah Somashekhar & Nottath Ramachandran & Jose Mathew
More informationResearch Article Study of Tool Wear and Overcut in EDM Process with Rotary Tool and Magnetic Field
Advances in Tribology Volume 212, Article ID 895918, 8 pages doi:1.1155/212/895918 Research Article Study of Tool Wear and Overcut in EDM Process with Rotary Tool and Magnetic Field Reza Teimouri and Hamid
More informationMULTI-RESPONSE OPTIMIZATION OF EDM PERFORMANCE CHARACTERISTICS USING RESPONSE SURFACE METHODOLOGY AND DESIRABILITY FUNCTION
VOL. 9, NO. 1, DECEMBER 014 ISSN 1819-6608 006-014 Asian Research Publishing Network (ARPN). All rights reserved. MULTI-RESPONSE OPTIMIZATION OF EDM PERFORMANCE CHARACTERISTICS USING RESPONSE SURFACE METHODOLOGY
More informationA Comparative Modeling and Multi- Objective Optimization in Wire EDM Process on H21 Tool Steel Using Intelligent Hybrid Approach
A Comparative Modeling and Multi- Objective Optimization in Wire EDM Process on H21 Tool Steel Using Intelligent Hybrid Approach Bikash Choudhuri *, Ruma Sen, Subrata Kumar Ghosh, S. C. Saha Mechanical
More informationA Review Paper on Rotary Electro-Discharge Machining
A Review Paper on Rotary Electro-Discharge Machining 1 Mr. Ganesh Pandurang Jadhav, 2 Dr. Narendra Narve 1 P.G.Student, 2 Professor Department Of Mechanical Engineering, JSPM Bhagwant Institute of Technology,
More informationFEM ANALYSIS WITH EXPERIMENTAL RESULTS TO STUDY EFFECT OF EDM PARAMETERS ON MRR OF AISI 1040 STEEL
FEM ANALYSIS WITH EXPERIMENTAL RESULTS TO STUDY EFFECT OF EDM PARAMETERS ON MRR OF AISI 1040 STEEL Imran Patel 1 & Prashant Powar 2 1PG Student, Department of Production Engineering, KIT s College of Engineering,
More informationNeuro-fuzzy model and Regression model a comparison study of MRR in Electrical discharge machining of D2 tool steel
Neuro-fuzzy model and Regression model a comparison study of MRR in Electrical discharge machining of D2 tool steel M. K. Pradhan*, and C. K. Biswas, Abstract In the current research, neuro-fuzzy model
More informationTHere is a heavy demand of the advanced materials with
Vol:3, No:9, 29 Neuro-fuzzy model and Regression model a comparison study of MRR in Electrical discharge machining of D2 tool steel M. K. Pradhan*, and C. K. Biswas, International Science Index, Mechanical
More information2. To compare results with a previous published work[6].
Predicting Material Removal Rate of EDM of 95WC/5NI Composites Fuzzy Logic Omar M Elmabrouk Industrial and Manufacturing Systems Engineering Department Benghazi University Benghazi, Libya omarelmabrouk@uobeduly
More informationExperimental Study on Parametric Optimization of Titanium based Alloy (Ti-6Al-4V) in Electrochemical Machining Process
Experimental Study on Parametric Optimization of Titanium based Alloy (Ti-6Al-4V) in Electrochemical Machining Process Pravin D.Babar Mechanical Engineering Department, Rajarambapu Institute of Technology
More informationEXPERIMENTAL INVESTIGATION OF MRR AND SURFACE ROUGHNESS OF EN-18 STEEL IN ECM
EXPERIMENTAL INVESTIGATION OF MRR AND SURFACE ROUGHNESS OF EN-18 STEEL IN ECM BY K SAYAN KUMAR (109ME0595) Under The Guidance of Prof. C.K.Biswas Department of Mechanical Engineering National Institute
More informationChapter 5 EXPERIMENTAL DESIGN AND ANALYSIS
Chapter 5 EXPERIMENTAL DESIGN AND ANALYSIS This chapter contains description of the Taguchi experimental design and analysis procedure with an introduction to Taguchi OA experimentation and the data analysis
More informationMaterials Science Forum Online: ISSN: , Vols , pp doi: /
Materials Science Forum Online: 2004-12-15 ISSN: 1662-9752, Vols. 471-472, pp 687-691 doi:10.4028/www.scientific.net/msf.471-472.687 Materials Science Forum Vols. *** (2004) pp.687-691 2004 Trans Tech
More informationResponse surface Methodology and Desirability Approach to Optimize EDM Parameters
, pp. 393-406 http://dx.doi.org/10.14257/ijhit.2016.9.4.34 Response surface Methodology and Desirability Approach to Optimize EDM Parameters ChittaranjanDas. V Department of Mechanical Engineering, R.V.R.&J.C.
More informationOPTIMIZATION OF PROCESS PARAMETERS IN ELECTROCHEMICAL DEBURRING OF DIE STEEL USING TAGUCHI METHOD
International Journal of Modern Manufacturing Technologies ISSN 2067 3604, Vol. IV, No. 1 / 2012 121 OPTIMIZATION OF PROCESS PARAMETERS IN ELECTROCHEMICAL DEBURRING OF DIE STEEL USING TAGUCHI METHOD Manoj
More informationThe Influence of EDM Parameters in Finishing Stage on Surface Quality, MRR and EWR
Research Journal of Applied Sciences, Engineering and Technology 4(10): 1287-1294, 2012 ISSN: 2040-7467 Maxwell Scientific Organization, 2012 Submitted: December 09, 2011 Accepted: December 26, 2011 Published:
More informationOptimization of Machining Process Parameters in Drilling of
Optimization of Machining Process Parameters in Drilling of CFRP Using Multi-Objective Taguchi Technique, TOPSIS and RSA Optimization of Machining Process Parameters in Drilling of CFRP Using Multi-Objective
More informationBuilding Energy Efficiency: Optimization of Building Envelope Using Grey-Based Taguchi
ISSN: -0 Vol. Issue, December - 0 Building Energy Efficiency: Optimization of Building Envelope Using Grey-Based Taguchi Samah K. Alghoul Ph.D., Assist. Prof. Dept. of Mechanical and Industrial Engineering
More informationArch. Metall. Mater. 62 (2017), 3,
Arch. Metall. Mater. 62 (2017), 3, 1803-1812 DOI: 10.1515/amm-2017-0273 K. SHUNMUGESH* #, K. PANNEERSELVAM** OPTIMIZATION OF DRILLING PROCESS PARAMETERS VIA TAGUCHI, TOPSIS AND RSA TECHNIQUES Carbon Fiber
More informationJournal of Chemical and Pharmaceutical Research, 2017, 9(10): Research Article
Available online www.jocpr.com Journal of Chemical and Pharmaceutical Research, 2017, 9(10):59-69 Research Article ISSN : 0975-7384 CODEN(USA) : JCPRC5 Experimental Investigation of Surface Roughness of
More informationOptimization Of Process Parameters In Drilling Using Taguchi Method
Optimization Of Process Parameters In Drilling Using Taguchi Method 1 P.Surendra, 2 B.Krishna Murthy, 3 M.V.Kiran Kumar 1 Associate Professor, 2 Assistant Professor, 3 Assistant Professor Department of
More informationApplication of Taguchi method in optimization of control parameters of grinding process for cycle time reduction Snehil A. Umredkar 1, Yash Parikh 2
Application of Taguchi method in optimization of control parameters of grinding process for cycle time reduction Snehil A. Umredkar, Yash Parikh 2 (Department of Mechanical Engineering, Symbiosis Institute
More informationOptimization of Process Parameters in CNC Drilling of EN 36
Optimization of Process Parameters in CNC ing of EN 36 Dr. K. Venkata Subbaiah 1, * Fiaz khan 2, Challa Suresh 3 1 Professor, Department of Mechanical Engineering, Andhra University, Visakhapatnam, Andhra
More informationProceedings of the International Conference on Advances in Production and Industrial Engineering
Proceedings of the International Conference on Advances in Production and Industrial Engineering 2015 250 Prediction of Material Removal in Electro Chemical Machining using Multiple Regression Analysis
More informationAnalysis and Mathematical Modeling of Wire EDM Process Parameters for Commercial Graphite by Using Response Surface Methodology
Advance Research and Innovations in Mechanical, Material Science, Industrial Engineering and Management - ICARMMIEM-201 7 Analysis and Mathematical Modeling of Wire EDM Process Parameters for Commercial
More informationEffect of Machining Parameters on Milled Natural Fiber- Reinforced Plastic Composites
Journal of Advanced Mechanical Engineering (2013) doi:10.7726/jame.2013.1001 Research Article Effect of Machining Parameters on Milled Natural Fiber- Reinforced Plastic Composites G Dilli Babu 1*, K. Sivaji
More informationA STUDY OF THE ACCURACY OF THE MICRO ELECTRICAL DISCHARGE MACHINING DRILLING PROCESS
A STUDY OF TE ACCURACY OF TE MICRO ELECTRICAL DISCARGE MACINING DRILLING PROCESS D.T. Pham, S.S. Dimov, S. Bigot, A. Ivanov, and K. Popov Manufacturing Engineering Centre, School of Engineering, Cardiff
More informationDrilling Mathematical Models Using the Response Surface Methodology
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:5 No:06 9 Drilling Mathematical Models Using the Response Surface Methodology Panagiotis Kyratsis, Nikolaos Taousanidis, Apostolos
More informationComparative Assessment of the Transient Temperature Response during Single-discharge Machining by Micro-EDM and LIP-MM Processes
Comparative Assessment of the Transient Temperature Response during Single-discharge Machining by Micro-EDM and LIP-MM Processes ICOMM 2014 No. 37 Ishan Saxena #1, Xiaochun Li 2, K. F. Ehmann 1 1 Department
More informationMULTI-RESPONSE ANALYSIS OF ELECTRO-CHEMICAL MACHINING PROCESS USING PRINCIPAL COMPONENT ANALYSIS
MULTI-RESPONSE ANALYSIS OF ELECTRO-CHEMICAL MACHINING PROCESS USING PRINCIPAL COMPONENT ANALYSIS K P Maity*, N K Verma Department of Mechanical Engineering National Institute of Technology, Rourkela-798
More informationAnalysis and Multi-objective Optimisation of Surface
American Journal of Mechanical Engineering, 014, Vol., No. 5, 130-14 Available online at http://pubs.sciepub.com/ajme//5/ Science and Education Publishing DOI:10.1691/ajme--5- Analysis and Multi-objective
More informationModelling Of Micro Electric Discharge Machining Using FEM
5 th International & 26 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 214) December 12 th 14 th, 214, IIT Guwahati, Assam, India Modelling Of Micro Electric Discharge Machining
More information