IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Realizing Potential of Graphite Powder in Enhancing Machining Rate in AEDM of...IDES Editor
Additive mixed electric discharge machining
(AEDM) is a recent innovation for enhancing the capabilities
of electrical discharge machining process. The objective of
present study is to realize the potential of graphite powder as
additive in enhancing machining capabilities of AEDM on
Inconel 718. Taguchi methodology has been adopted to plan
and analyze the experimental results. L36 Orthogonal Array
has been selected to conduct experiments. Peak current, Pulse
on time, duty cycle, gap voltage, retract distance and
concentration of fine graphite powder added into the dielectric
fluid were chosen as input process variables to study
performance in terms of material removal rate. The ANOVA
analysis identifies the most important parameters to maximize
material removal rate. The recommended best parametric
settings have been verified by conducting confirmation
experiments. From the present experimental study it is found
that addition of graphite powder enhances machining rate
appreciably. Machining rate is improved by 26.85% with 12g/
l of fine graphite powder at best parametric setting.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Multi-Response Optimization of WEDM Process Parameters of Monel 400 using Int...ijceronline
Non-traditional machining processes such as Wire Electric Discharge Machining (WEDM) are increasingly been employed to machine difficult-to-machine materials. Monel 400 an alloy of Nickel and Copper is taken in this study and it is cut through Wire Electric Discharge Machining process. It is utilized mainly in corrosion resistant applications. Further, the process parameters are optimized to get the desired machining conditions which can improve the quality of machining. Design of Experiments is done through Central Composite Design (CCD). Response Surface Methodology (RSM) and Genetic Algorithm (GA) which is an evolutionary algorithm are the techniques employed for the optimization of parameters in WEDM. The multi response optimization for achieving maximum material removal rate (MRR) and minimum surface roughness, the optimum process parameters are found to be ‘Current’ of 2.031 A, ‘T-On’ of 3 µs, ‘T-Off’ of 10 µs, the obtained maximum MRR is 6.339 mm 3 /min and minimum surface roughness is 1.846 µm.
Optimization of Cutting Rate for EN 1010 Low Alloy Steel on WEDM Using Respon...IJAEMSJORNAL
EN 1010is a low-carbon steel alloy with 0.10% carbon content. It is known for its fairly low strength and low ductility; however, it can be tempered to increase strength. Machinability of EN 1010 carbon steel is measured to be fairly good. EN 1010 is commonly used for cold headed fasteners, rivets and bolts, in addition to structural, construction and automotive applications such as fenders, pans, nails and transmission covers. Wire Electric Discharge Machine (WEDM) seems to be a good option for machining the complicated profiles. This paper, find effects of various process parameters of Wire EDM such as pulse on time (Ton), pulse off time(Toff), peak current (Ip) and servo voltage (Sv) for analysis of cutting rate (CR) while machining EN 1010. Central Composite Design is used to plan the design of experiment. The output response variable being cutting rate will be measured for all number of experiments conducted. The optimal parameter level combination would be analysed which gives desired cutting rate. These optimized values of different parameters would then be used in execution the machining operation in order to obtain the necessary outputs.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Optimization of WEDM Process Parameters on Titanium Alloy Using Taguchi MethodIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Realizing Potential of Graphite Powder in Enhancing Machining Rate in AEDM of...IDES Editor
Additive mixed electric discharge machining
(AEDM) is a recent innovation for enhancing the capabilities
of electrical discharge machining process. The objective of
present study is to realize the potential of graphite powder as
additive in enhancing machining capabilities of AEDM on
Inconel 718. Taguchi methodology has been adopted to plan
and analyze the experimental results. L36 Orthogonal Array
has been selected to conduct experiments. Peak current, Pulse
on time, duty cycle, gap voltage, retract distance and
concentration of fine graphite powder added into the dielectric
fluid were chosen as input process variables to study
performance in terms of material removal rate. The ANOVA
analysis identifies the most important parameters to maximize
material removal rate. The recommended best parametric
settings have been verified by conducting confirmation
experiments. From the present experimental study it is found
that addition of graphite powder enhances machining rate
appreciably. Machining rate is improved by 26.85% with 12g/
l of fine graphite powder at best parametric setting.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Multi-Response Optimization of WEDM Process Parameters of Monel 400 using Int...ijceronline
Non-traditional machining processes such as Wire Electric Discharge Machining (WEDM) are increasingly been employed to machine difficult-to-machine materials. Monel 400 an alloy of Nickel and Copper is taken in this study and it is cut through Wire Electric Discharge Machining process. It is utilized mainly in corrosion resistant applications. Further, the process parameters are optimized to get the desired machining conditions which can improve the quality of machining. Design of Experiments is done through Central Composite Design (CCD). Response Surface Methodology (RSM) and Genetic Algorithm (GA) which is an evolutionary algorithm are the techniques employed for the optimization of parameters in WEDM. The multi response optimization for achieving maximum material removal rate (MRR) and minimum surface roughness, the optimum process parameters are found to be ‘Current’ of 2.031 A, ‘T-On’ of 3 µs, ‘T-Off’ of 10 µs, the obtained maximum MRR is 6.339 mm 3 /min and minimum surface roughness is 1.846 µm.
Optimization of Cutting Rate for EN 1010 Low Alloy Steel on WEDM Using Respon...IJAEMSJORNAL
EN 1010is a low-carbon steel alloy with 0.10% carbon content. It is known for its fairly low strength and low ductility; however, it can be tempered to increase strength. Machinability of EN 1010 carbon steel is measured to be fairly good. EN 1010 is commonly used for cold headed fasteners, rivets and bolts, in addition to structural, construction and automotive applications such as fenders, pans, nails and transmission covers. Wire Electric Discharge Machine (WEDM) seems to be a good option for machining the complicated profiles. This paper, find effects of various process parameters of Wire EDM such as pulse on time (Ton), pulse off time(Toff), peak current (Ip) and servo voltage (Sv) for analysis of cutting rate (CR) while machining EN 1010. Central Composite Design is used to plan the design of experiment. The output response variable being cutting rate will be measured for all number of experiments conducted. The optimal parameter level combination would be analysed which gives desired cutting rate. These optimized values of different parameters would then be used in execution the machining operation in order to obtain the necessary outputs.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Optimization of WEDM Process Parameters on Titanium Alloy Using Taguchi MethodIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
APPLICATION OF GREY RELATIONAL ANALYSIS FOR MULTI VARIABLE OPTIMIZATION OF PR...IAEME Publication
The present work deals with a simple approach which predicts the optimum setting
of process parameters of drilling operation on Polymer Based Glass Fiber (PBGF)
composite. The process parameters selected are drill angle (DA), Drill diameter (DD),
Material Thickness (MT), Speed (N) and Feed (f). The output parameters are Thrust,
Torque, Surface Roughness and Delamination. Three levels of each input parameters
are considered. Taguchi’s L27 array is used to set the process parameters. Gray
relational analysis (GRA) is used to find the optimum value of process parameters.
Conduction of ANOVA on GRA shown the significance of each factor on the process
output. A conformation test conducted revealed that the setting of parameters ensures
optimum output
Modeling of wedm process for complex shape using multilayer perceptron and re...eSAT Journals
Abstract
Wire cut electric discharge machining is the present days requirement in manufacturing the intricate and complex shape parts as required in the modern industrial products. The process being complex in nature for control over the machining process parameters. In the present study Multilayer perceptron (MLP) model is developed to predict the Material removal rate. The mathematical regression model is also developed by using Response Surface Methodology (RSM) to establish the relationshIp between the MRR and input process parameters like pulse on time (Ton), Pulse off time (Toff), Peak current (IP) and Servo voltage (SV). The predicted value by using MLP and RSM were compared with the experimental values. The average percentage errors are found to be 1.29 and -0.36527 for MLP and RSM respectively. It is observed that the predicted values with RSM are closer to experimental values as compared to MLP model. Key Words: WEDM, Response Surface Methodology, Neural Network, Multi Layer Perception, Material Removal Rate, Surface Roughness
A Comparison of Optimization Methods in Cutting Parameters Using Non-dominate...Waqas Tariq
Since cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product the determination of optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool geometry is one of vital modules in process planning of metal parts. With use of experimental results and subsequently, with exploitation of main effects plot, importance of each parameter is studied. In this investigation these parameters was considered as input in order to optimized the surface finish and tool life criteria, two conflicting objectives, as the process performance simultaneously. In this study, micro genetic algorithm (MGA) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were compared with each other proving the superiority of Non-dominated Sorting Genetic Algorithm over micro genetic since Non-dominated Sorting Genetic Algorithm results were more satisfactory than micro genetic algorithm in terms of optimizing machining parameters.
A comparative study of PSO, GSA and SCA in parameters optimization of surface...journalBEEI
The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions.
Evaluation of Optimal Parameters for Surface Roughness Using Single Objective...IJERA Editor
Medium carbon steel EN8 has a wide variety of applications in oil, gas and tool industries. It is most commonly
used where high tensile strength is required. In the present work, an attempt has been made to explore the effect
of machining parameters on Surface Roughness (Ra). Taguchi’s single objective optimization technique is used
to optimize the machining parameters in EDM for EN8 steel. For the experimentation Taguchi’s L27
Orthogonal array has been used. The input parameters selected are Pulse on time (PON), Pulse off time (POFF),
Wire tension (WT) and Wire feed (WF). From the Taguchi results, optimal combination of machining
parameters for Surface Roughness is found at Pulse-on time (PON) level 3(131μs), Pulse-off time (POFF) level 2
(58μs), Wire tension (WT) level 1(2 Kg-f) and Wire feed rate (WF) level 1(4m/min). ANOVA was used to find
the influence of machining parameters on Surface Roughness. From the results, it is found that wire feed rate
(WF) has high influence (F = 47.16) and Pulse-off time (TOFF) has very low influence (F = 1.57) in effecting the
Surface Roughness. Regression model for Surface Roughness has been prepared by using MINITAB-16
software. Experimental values and Regression values of Surface Roughness were compared and from the graph,
it is clear that both the values are very close to each other. Hence, Regression model prepared is accurate,
adequate and it can be used for the prediction of Surface Roughness.
Optimization of edm process parameters using taguchi method a revieweSAT Journals
Abstract
Electrical discharge machining is assessed on the basis of Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (SR). Process parameters that mostly affected the EDM Process are Pulse on Time, Pulse off Time, Discharge Current, Arc Gap and Duty Cycle. This paper reviews research for the optimization and improvement of various performance parameters measured in the experimentation on EDM by using Taguchi technique. In the study the main objectives of optimization is to minimize the tool wear rate (TWR) and surface roughness, and to maximize the material removal rate (MRR).Taguchi Method is widely used in the industry to optimize and improve various performance parameters associated with different machining processes. This paper also deals with the review of some of the work reported with the use of Taguchi method in last two decades.
Keywords: - EDM, Wire EDM, MRR, RWR, TWR, SR, Taguchi Technique
Optimization of Surface Roughness for EN 1010 Low Alloy Steel on WEDM Using R...IJAEMSJORNAL
The term steel is used for many different alloys of iron. All steels cover small amounts of carbon and manganese. There do exist many types of steels which are(among others) plain carbon steel, stainless steel, alloysteel and tool steel. Carbon steel is the most extensively used kind of steel. The properties of carbon steel depend mainly on the amount of carbon it contains. Maximum carbon steel has a carbon content of less than 1%. Carbon steel is made into an extensive range of products, including structural beams, car bodies. In fact, there are 3 types of plain carbon steel namely low carbon steel, medium carbon steel, high carbon steel. It is good to exact that plain carbon steel is a type of steel having a maximum carbon content of 1.5% along with small percentages of silica, Sulphur, phosphorus and manganese. EN 1010 is a lowest amount of carbonalloy steel alloy with carbon content of 0.10%. Machineability of EN 1010 carbon steel is measured to be fairly good. EN 1010 is usually used for rivets and bolts, construction and automotive applications such as pans, nails and transmission cover. The objective of paper is to study the effect of process parameters namely pulse on time, pulse off time, peak current and servo voltage on surface roughness(SR).The effect of process parameters on productivity and accuracy facts is material dependent. To study parametric effect on Surface Roughness a Central Composite design approach of response surface methodology (RSM) is used to plan and study the experiments. The mathematical relationships between WEDM input process parameters and response parameter namely surface roughness is established to determine optimal values of surface roughness mathematically and graphically.The Analysis of variance (ANOVA) is performed to find statistically significant process parameters. Interaction effects of process parameters on surface roughness are analysed using statistical and graphical representations.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
APPLICATION OF GREY RELATIONAL ANALYSIS FOR MULTI VARIABLE OPTIMIZATION OF PR...IAEME Publication
The present work deals with a simple approach which predicts the optimum setting
of process parameters of drilling operation on Polymer Based Glass Fiber (PBGF)
composite. The process parameters selected are drill angle (DA), Drill diameter (DD),
Material Thickness (MT), Speed (N) and Feed (f). The output parameters are Thrust,
Torque, Surface Roughness and Delamination. Three levels of each input parameters
are considered. Taguchi’s L27 array is used to set the process parameters. Gray
relational analysis (GRA) is used to find the optimum value of process parameters.
Conduction of ANOVA on GRA shown the significance of each factor on the process
output. A conformation test conducted revealed that the setting of parameters ensures
optimum output
Modeling of wedm process for complex shape using multilayer perceptron and re...eSAT Journals
Abstract
Wire cut electric discharge machining is the present days requirement in manufacturing the intricate and complex shape parts as required in the modern industrial products. The process being complex in nature for control over the machining process parameters. In the present study Multilayer perceptron (MLP) model is developed to predict the Material removal rate. The mathematical regression model is also developed by using Response Surface Methodology (RSM) to establish the relationshIp between the MRR and input process parameters like pulse on time (Ton), Pulse off time (Toff), Peak current (IP) and Servo voltage (SV). The predicted value by using MLP and RSM were compared with the experimental values. The average percentage errors are found to be 1.29 and -0.36527 for MLP and RSM respectively. It is observed that the predicted values with RSM are closer to experimental values as compared to MLP model. Key Words: WEDM, Response Surface Methodology, Neural Network, Multi Layer Perception, Material Removal Rate, Surface Roughness
A Comparison of Optimization Methods in Cutting Parameters Using Non-dominate...Waqas Tariq
Since cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product the determination of optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool geometry is one of vital modules in process planning of metal parts. With use of experimental results and subsequently, with exploitation of main effects plot, importance of each parameter is studied. In this investigation these parameters was considered as input in order to optimized the surface finish and tool life criteria, two conflicting objectives, as the process performance simultaneously. In this study, micro genetic algorithm (MGA) and Non-dominated Sorting Genetic Algorithm (NSGA-II) were compared with each other proving the superiority of Non-dominated Sorting Genetic Algorithm over micro genetic since Non-dominated Sorting Genetic Algorithm results were more satisfactory than micro genetic algorithm in terms of optimizing machining parameters.
A comparative study of PSO, GSA and SCA in parameters optimization of surface...journalBEEI
The selection of parameters in grinding process remains as a crucial role to guarantee that the machined product quality is at the minimum production cost and maximum production rate. Therefore, it is required to utilize more advance and effective optimization methods to obtain the optimum parameters and resulting an improvement on the grinding performance. In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. The efficiency of the three algorithms are evaluated and comparedwith previous results obtained by other optimization methods on similar studies.The experimental results showed that PSO algorithm achieves better optimization performance in the aspect of convergence rate and accuracy of best solution.Whereas in the comparison of results of previous researchers, the obtained result of PSO proves that it is efficient in solving the complicated mathematical model of surface grinding process with different conditions.
Evaluation of Optimal Parameters for Surface Roughness Using Single Objective...IJERA Editor
Medium carbon steel EN8 has a wide variety of applications in oil, gas and tool industries. It is most commonly
used where high tensile strength is required. In the present work, an attempt has been made to explore the effect
of machining parameters on Surface Roughness (Ra). Taguchi’s single objective optimization technique is used
to optimize the machining parameters in EDM for EN8 steel. For the experimentation Taguchi’s L27
Orthogonal array has been used. The input parameters selected are Pulse on time (PON), Pulse off time (POFF),
Wire tension (WT) and Wire feed (WF). From the Taguchi results, optimal combination of machining
parameters for Surface Roughness is found at Pulse-on time (PON) level 3(131μs), Pulse-off time (POFF) level 2
(58μs), Wire tension (WT) level 1(2 Kg-f) and Wire feed rate (WF) level 1(4m/min). ANOVA was used to find
the influence of machining parameters on Surface Roughness. From the results, it is found that wire feed rate
(WF) has high influence (F = 47.16) and Pulse-off time (TOFF) has very low influence (F = 1.57) in effecting the
Surface Roughness. Regression model for Surface Roughness has been prepared by using MINITAB-16
software. Experimental values and Regression values of Surface Roughness were compared and from the graph,
it is clear that both the values are very close to each other. Hence, Regression model prepared is accurate,
adequate and it can be used for the prediction of Surface Roughness.
Optimization of edm process parameters using taguchi method a revieweSAT Journals
Abstract
Electrical discharge machining is assessed on the basis of Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (SR). Process parameters that mostly affected the EDM Process are Pulse on Time, Pulse off Time, Discharge Current, Arc Gap and Duty Cycle. This paper reviews research for the optimization and improvement of various performance parameters measured in the experimentation on EDM by using Taguchi technique. In the study the main objectives of optimization is to minimize the tool wear rate (TWR) and surface roughness, and to maximize the material removal rate (MRR).Taguchi Method is widely used in the industry to optimize and improve various performance parameters associated with different machining processes. This paper also deals with the review of some of the work reported with the use of Taguchi method in last two decades.
Keywords: - EDM, Wire EDM, MRR, RWR, TWR, SR, Taguchi Technique
Optimization of Surface Roughness for EN 1010 Low Alloy Steel on WEDM Using R...IJAEMSJORNAL
The term steel is used for many different alloys of iron. All steels cover small amounts of carbon and manganese. There do exist many types of steels which are(among others) plain carbon steel, stainless steel, alloysteel and tool steel. Carbon steel is the most extensively used kind of steel. The properties of carbon steel depend mainly on the amount of carbon it contains. Maximum carbon steel has a carbon content of less than 1%. Carbon steel is made into an extensive range of products, including structural beams, car bodies. In fact, there are 3 types of plain carbon steel namely low carbon steel, medium carbon steel, high carbon steel. It is good to exact that plain carbon steel is a type of steel having a maximum carbon content of 1.5% along with small percentages of silica, Sulphur, phosphorus and manganese. EN 1010 is a lowest amount of carbonalloy steel alloy with carbon content of 0.10%. Machineability of EN 1010 carbon steel is measured to be fairly good. EN 1010 is usually used for rivets and bolts, construction and automotive applications such as pans, nails and transmission cover. The objective of paper is to study the effect of process parameters namely pulse on time, pulse off time, peak current and servo voltage on surface roughness(SR).The effect of process parameters on productivity and accuracy facts is material dependent. To study parametric effect on Surface Roughness a Central Composite design approach of response surface methodology (RSM) is used to plan and study the experiments. The mathematical relationships between WEDM input process parameters and response parameter namely surface roughness is established to determine optimal values of surface roughness mathematically and graphically.The Analysis of variance (ANOVA) is performed to find statistically significant process parameters. Interaction effects of process parameters on surface roughness are analysed using statistical and graphical representations.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Influence of process parameters on MRR in EDM of AISI D2 Steel: a RSM approachMohan Kumar Pradhan
Response Surface Methodology (RSM) is used to investigate the
effect of three controllable input variables namely: discharge current, pulse duration,
and pulse off time on material removal rate (MRR) in EDM process. To study the
proposed second-order polynomial model for MRR, a central composite design is
used to estimation the model coefficients of the three factors, which are believed to
influence the MRR in EDM process. Experiments were conducted on AISI D2 tool
steel with copper electrode. The response is modeled using RSM on the experimental
data. The significant coefficients are obtained by performing analysis of variance
(ANOVA) at 5% level of significance. It is found that discharge current, pulse duration,
and pulse off time and few of their interactions have significant effect on the MRR.
The model sufficiency is very satisfactory as the coefficient of determination (R2) is
found to be 97.6%.
IJCER (www.ijceronline.com) International Journal of computational Engineeri...ijceronline
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INFLUENCE OF PROCESS PARAMETERS ON SURFACE ROUGHNESS AND MATERIAL REMOVAL RAT...ijmech
Optimization of machining parameters is very valuable to maintain the accuracy of the components and
obtain cost effective Machining.MRR (material removal rate) and surface roughness is playing primary
role in manufacturing using contemporary CNC (computer numerical controlled) machines, in the case of
mass manufacturing. In present study experimental and work is done for optimization of process
parameters. In experimental work total 32 experiments are designed according DOE method “Mixed
taguchi”. Three factors are selected for experimental work. Depth of cut, speed and feed rate is selected
factors for experimental work. All experiments are carried out in CIPET, Jaipur. Two responses are find
out in this work and are following: first one is material removal rate (MRR) and second response is surface
roughness (Ra) measurement. An artificial neural network is ‘Feed Forward Back Propagation’ type
model of developing the analysis and prediction of surface roughness and MRR with relationship between
all input process parameters
Investigation and modelling of edm process parameters in machining of incoloy...eSAT Journals
Abstract The experimentation has been performed on EDM for the modelling and optimization of the process parameters. In this work modelling of the processes are done by artificial neural networking and optimization by genetic algorithm. For fitness function regression analysis has been performed. Design of experiment with mixed level L18 orthogonal array has been considered. All 18 experiments were performed on INCOLOY-800. Copper as an electrode considered. In this work TWR considered as the response variable. Dielectric fluid with two level; where current, pulse on time and gap voltage considered with three levels as the process parameters. 4-17-1-1 network considered in ANN by feed forward back propagation for process modelling. Two types of dielectric fluid considered as kerosene and EDM oil. For multi objective-optimization Genetic Algorithm used (GA). Keywords –Artificial neural network, genetic algorithm, machining time, material removal rate
Estimation Of Optimum Dilution In The GMAW Process Using Integrated ANN-SAIJRES Journal
To improve the corrosion resistant properties of carbon steel usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using Gas Metal Arc Welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, Artificial Neural Network (ANN) and Simulated Annealing Algorithm (SA) techniques were integrated labels as integrated ANN-SA to estimate optimal process parameters in GMAW to get optimum dilution.
PROCESS PARAMETER OPTIMISATION IN WEDM OF HCHCR STEEL USING TAGUHI METHOD AND...IAEME Publication
Wire Electrical Discharge Machining (WEDM) is used as a valuable machining tool in the world of non-traditional machining due to various features which includes higher degree of accuracy, fine surface quality and good productivity. WEDM consists of large number of process parameters,
thus it is difficult to obtain a combination of optimum parameters which provides higher accuracy. Optimization of a single response is often carried out with the well known technique Taguchi method. This method results in the solution which gives optimum value of each response
THE EFFECT OF DIFFERENT WIRE ELECTRODES ON THE MRR OF MS WORKPIECE USING WEDM...IAEME Publication
Wire electrical discharge machining (WEDM) is a specialized thermal machining process which is capable of accurate machining of parts which have varying hardness, complex shapes and sharp edges that are hard to be machined by the traditional machining processes. . Predictions on the
Material Removal Rate of workpieces in WEDM have been reported in the past. In the present study an analysis has been done to evaluate the Material Removal Rate of MS workpiece using WEDM process with different types of wire electrodes.
Artificial Intelligence based optimization of weld bead geometry in laser wel...IJMER
This paper reports on a modeling and optimization of laser welding of aluminum-magnesium alloy thickness of 1.7mm. Regression analysis is used for modeling and Genetic algorithm is used for optimize the process parameters.The input values for the regression methods is taken according the Taguchi based orthogonal array. A software named Computer aided Robust Parameter Genetic Algorithm CARPGA has been developed in MATLAB 2013 which combine all of these methodologies. This software has been validated with some published paper.
Experimental Study of Surface Parameters of EN31 on Powder Mixed EDM using Ta...ijsrd.com
PEDM has become an effective method of machining extremely tough and brittle electrically conductive materials. It is widely used in the process of making moulds and dies and sections of complex geometry and intricate shapes. The work piece material selected in this experiment is EN 31 taking into account its wide usage in industrial applications. In today’s world 304 stainless steel contributes to almost half of the world’s production and consumption for industrial purposes. The input variable parameters are type of powder, current, pulse on time and powder concentration. Taguchi method is applied to create an L18 orthogonal array of input variables using the Design of Experiments (DOE). The effect of the variable parameters mentioned above upon machining characteristics such as Material Removal Rate (MRR) and Surface Roughness (SR) is studied and investigated. The tool material is copper. All the calculations are made with the help of MINITAB 16 software. Dielectric used for experimentation is kerosene. Two powders silicon carbide and boron carbide of 70 mesh is used. Most influence factor for MRR observed is powder concentration with 49.12 % contribution. For SR peak current with contribution of 43.4 % plays a n important role.
Micron range complex structure in micro electrochemical machining- a revieweSAT Journals
Abstract
The major problem in the micro-manufacturing is concerned with achieving the good dimensional accurate products with the better surface finish, high MRR, no tool wear, absence of stress and no heat-affected zone. Micro-machining proved itself as a promising solution of this major problem. In recent days, industries are regularly looking for fabricating the micro-components which can be able to perform their complex functions in the sensitive areas of electronics, automotive, biomedical and optics. Now a day for miniature components micro-machining plays a very important role, its techniques are excellent to machine any complex shapes with good accuracy and bright surface finish. Material with any value of the hardness can be machined easily with all the offered advantages of micro-machining in the electrochemical micro-machining process (EMM). In this article; review of different methodologies and effect of machining parameters were studied along with different electrolytes; which plays a significant role in electro chemical micro-machining. The objective of this study is to know about the optimum micro-machining parameters for the EMM process and it is also much important to find out the research gap through the different studies. In this study, it has been found out MRR and overcut are depends upon the voltage, electrolyte concentration, IEG, pulse ON/OFF time, pulse duration, pulse frequency, RPM of the tool and flow rate of electrolyte. The proper selections of parameters in EMM are essentials for achieving the overall improvement in the micro-machining operation.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Epistemic Interaction - tuning interfaces to provide information for AI support
Ll2519861993
1. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
Process Parameters Optimization Of Micro Electric Discharge
Machining Process Using Genetic Algorithm
Ruben Phipon* and B.B.Pradhan
Department of Mechanical Engineering,
Sikkim Manipal Institute of Technology,
P.O. Majitar 737136, Sikkim, India.
ABSTRACT
Micro Electric Discharge Machining suitable optimization technique to search for correct
(micro EDM) is a non-traditional machining parameter values for the desired responses.
process which can be used for drilling micro Hung et al. [1] while using a helical micro-tool
holes in high strength to weight ratio materials electrode with Micro-EDM combined with
like Titanium super alloy. However, the process ultrasonic vibration found that it can substantially
control parameters of the machine have to be set reduce the EDM gap, variation between entrance
at an optimal setting in order to achieve the and exit and machining time, especially during deep
desired responses. This present research study micro-hole drilling. Jeong et al. [2] proposed a
deals with the single and multiobjective geometric simulation model of EDM drilling
optimization of micro EDM process using process with cylindrical tool to predict the
Genetic Algorithm. Mathematical models using geometries of tool and drilled hole matrix. The
Response Surface Methodology (RSM) is used to developed model can be used in offline
correlate the response and the parameters. The compensation of tool wear in the fabrication of a
desired responses are minimum tool wear rate blind hole..
and minimum overcut while the independent Mukherjee and Ray [3] presented a generic
control parameters considered are pulse on time, framework for parameter optimization in metal
peak current and flushing pressure. In the cutting processes for selection of an appropriate
multiobjective problem, the responses conflict approach. In practice, a robust optimization
with each other. This research provides a Pareto technique which is immune with respect to
optimal set of solution points where each solution production tolerances is desirable [4]. Karthikeyan
is a non dominated solution among the group of et al. [5] conducted general factorial experiments to
predicted solution points thus allowing flexibility provide an exhaustive study of parameters on
in operating the machine while maintaining the material removal rate (MRR) and tool wear rate
standard quality. (TWR) while investigating performance of micro
electric discharge milling process. Taguchi method
Keywords: Micro electric discharge machining is used for experiment design to optimize the cutting
(micro EDM), Response Surface methodology parameters [6]. Experimental methods increase the
(RSM), Genetic Algorithm (GA), Pareto Optimal. cost of investigation and at times are not feasible to
perform all the experiments specially when the
1. INTRODUCTION number of parameters and their levels are more.
Micro-EDM is a recently developed RSM is employed to design the experiments with a
process which is used to produce micro-parts in the reduced number of experimental runs to achieve
range of 50μm -100μm. In this process, metal is optimum responses [7]. Lalwani et al. [8] applied
removed from the workpiece by melting and RSM to investigate the effect of cutting parameters
vaporization due to pulse discharges that occur in a on surface roughness in finish hard turning of
small gap between the workpiece and the electrode. MDN250 steel using coated ceramic tool.
It is a novel machining process used for fabrication Yildiz [9] compared state-of-the-art
of a micro-metal hole and can be used to machine optimization techniques to solve multi-pass turning
hard electrically conductive materials like Titanium optimization problems. The results show the
super alloy. The characteristic of non-contact superiority of the hybrid approach over the other
between the tool and the work piece in this process techniques in terms of convergence speed and
eliminates the chance of stress being developed on efficiency. Yusup et al. [10] discussed evolutionary
the work piece by the cutting tool force. techniques and basic methodology of each technique
However, to achieve the desired responses, in optimizing machining process parameters for
the independent control parameters which affect the both traditional and modern machining. Application
responses are to be set at an optimal value. Such of evolutionary techniques in optimizing machining
problems can be solved by first developing process parameters positively gives good results as
mathematical models correlating the responses and observed in the literature. Samanta and Chakraborty
the parameters. The second step is to choose a [11] proved the applicability and suitability of
1986 | P a g e
2. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
evolutionary algorithm in enhancing the Table 1 Coded and Actual control parameter values
performance measures of nontraditional machining at different levels
processes. Jain et al. [12] used GA for optimization Levels
of process parameters of mechanical type advanced 1 2 3 4 5
machining processes. Traditional optimization Coded -1.682 -1 0 1 1.682
methods are not suitable to solve problems where value
the formulated objective functions and constraints Pulse-on- 1 5 12 18 22
are very complicated and implicit functions of the time (µs)
decision variables.. Peak 0.4 0.7 1.2 1.7 2.0
Unlike conventional optimization current (A)
techniques, GA is a robust, global and can be Flushing 0.1 0.2 0.3 0.4 0.5
applied without recourse to domain-specific pressure
heuristics. Tansela et al. [13] proposed Genetically (Kg/cm2)
Optimized Neural Network System (GONNS) for
selection of optimal cutting conditions for micro end Table 2 Design of experiments matrix showing
milling operation. Singh and Rao [14] presented a coded values and observed responses
multi-objective optimization technique based on GA Coded values of parameters Actual values of Responses
to optimize the cutting parameters in turning
processes since undertaking frequent tests or many Sl. Pulse Peak Flushin Tool wear Overcut
experimental runs is not economically justified. Zain No on current g rate (mm)
et al [15] applied GA to optimize cutting conditions time (A) pressure (mg/min)
for minimizing surface roughness in end milling (µs) (Kg/cm2
machining process. Ghoreishi et al [16] applied GA )
for solving multi-objective optimization problems in
Robust Control of Distillation Column. Hence, due
1 -1 -1 -1 0.00033 0.0510
to the multifacet advantages of GA, an attempt has
2 1 -1 -1 0.00040 0.0390
been made to optimize the micro EDM process in
3 -1 1 -1 0.00047 0.0455
this research paper using this technique. In this
present research work in order to simultaneously 4 1 1 -1 0.00136 0.0340
optimize both the conflicting objectives, multi 5 -1 -1 1 0.00149 0.0490
objective GA is used to predict the non dominated 6 1 -1 1 0.00127 0.0367
Pareto optimal set of solution while drilling 7 -1 1 1 0.00062 0.0415
microholes in a Titanium super alloy. 8 1 1 1 0.00123 0.0297
9 -1.682 0 0 0.00062 0.0665
2. PROCESS MODELLING 10 1.682 0 0 0.00112 0.0503
2.1 RSM Modeling 11 0 -1.682 0 0.00066 0.0321
Pradhan and Bhattacharya [17] developed 12 0 1.682 0 0.00089 0.0195
mathematical models as shown by equations 1 and 2 13 0 0 -1.682 0.00060 0.0385
below based on second order polynomial equation 14 0 0 1.682 0.00150 0.0372
for correlating the interactions of micro EDM 15 0 0 0 0.00081 0.0402
control parameters, such as pulse on time, peak 16 0 0 0 0.00074 0.0382
current and flushing pressures and their effects on 17 0 0 0 0.00077 0.0399
some responses, such as tool wear rate and overcut 18 0 0 0 0.00078 0.0400
during micro hole machining of titanium alloy (Ti– 19 0 0 0 0.00082 0.0410
6Al–4V). 20 0 0 0 0.00078 0.0412
Table 1 lists the values for process control
parameters of pulse on time, peak current and The mathematical model correlating the tool wear
flushing pressures with five levels for each rate with the process control parameters is
parameter. A sum of twenty experimental runs is developed as:
designed using Center composite design. The
combinatorial effects of process control parameters Yu(twr) = 0.000708 + 0.000070(x1) - 0.000058(x2) +
at different levels on the measured response are 0.000296(X3) + 0.000011(x12) -
listed in Table 2.
0.000004(x22)+0.000095(x32)+0.000112(x1x2)-
0.000038(x1x3)–0.000252(x2x3). (1)
Similarly, the mathematical model for overcut is
developed as:
1987 | P a g e
3. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
Yu(oc) = 0.044513 - 0.006398(x1) - 0.0035(x2) -
-3
0.001071(x3)+0.001980(x12)-0.005609(x22)- x 10 Best: 0.00082663 Mean: 0.0031704
minimum overcut (mg/min)
0.000841(x32) + 0.000054(x1x2)- 6
Best fitness
0.00002(x1x3)-0.0005(x2x3).
Mean fitness
(2) 4
Where x1, x2 and x3 are pulse on time, peak
current and flushing pressure and Yu(twr) and 2
Yu(oc) are the responses for tool wear rate and
overcut respectively. The effects of linear, higher
order and the interaction of the independent process 0
0 5 10 15
variables are represented in equations (1) and (2).
Generation
Current Best Individual
3. SINGLE OBJECTIVE OPTIMIZATION 1
control parameter values
3.1. Optimization using GA
Genetic algorithm is an evolutionary
algorithm which applies the idea of survival of the
fittest amongst an interbreeding population to create 0.5
a robust search strategy. Initially a finite population
of solutions to a specified problem is maintained. It
then iteratively creates new populations from the old
by ranking the solutions according to their fitness
0
values and interbreeding the fittest to create new 1 2 3
offsprings which are optimistically closer to the Independent control parameters
optimum solution to the problem at hand. It uses
only the fitness value and no other knowledge is Fig. 1 GA predicted plot for minimum tool wear
required for its operation. It is a robust search rate and the control parameter values
technique different to the problem solving methods The results predicted using GA for
used by more traditional algorithms which tend to minimum tool wear rate is listed in Table 3. Trial
be more deterministic in nature and get stuck up at and error method for the selection of initial
local optima. As each generation of solutions is population size found the best result when the initial
produced, the weaker ones fade away without population size of 20 was chosen.
producing offsprings, while the stronger mate, Table 3 GA predicted results for minimum tool
combining the attributes of both parents, to produce wear rate
new and perhaps unique offsprings to continue the
cycle. Occasionally, mutation is introduced into one Control parameters
of the solution strings to further diversify the Trial Tool wear
population in search for a better solution. number Pulse Peak Flushing rate
The present research work optimizes the on current pressure (mg/min)
desired response and control parameters by writing time (A)
the mathematical models as developed in equations (µs) (Kg/cm2)
1 and 2 as .M-files and then solved by GA using the
MATLAB software. The initial population size 1 18 1.7 0.4 0.00195386
considered while running the GA is 20. A test of 10 2 18 1.7 0.4 0.00199364
runs has been conducted and the results are listed in 3 18 1.7 0.4 0.00225604
Tables 3 and 4 for minimum tool wear rate and 4 12 1.2 0.3 0.00285234
minimum overcut respectively. 5 12 1.2 0.3 0.00452525
The GA predicted value of minimum tool 6 12 1.2 0.3 0.00625264
wear rate and the corresponding control parameter 7 5 0.7 0.2 0.00975433
values are shown in Figure 1. It is observed from the 8 5 0.7 0.2 0.00094524
figure that the best minimum tool wear rate 9 1 0.4 0.1 0.00089732
predicted using GA is 0.00082663 mg/min with the 10 1 0.4 0.1 0.00082663
corresponding control parameter values of 1µs for
pulse on time, 0.4 A for peak current and 0.1
kg/cm2. Similarly, the GA predicted value of
minimum overcut and the corresponding control
parameter values are shown in Figure 2. The GA
predicted value of minimum overcut and the
corresponding control parameter values are shown
in Figure 2. It is observed from the figure that the
1988 | P a g e
4. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
minimum overcut predicted using GA is
0.00098289 mm with the corresponding control Table 4 GA predicted results for minimum overcut
parameter values of 1.5µs for pulse on time, 1.9 A
for peak current and 0.5 kg/cm2. The results Control parameters
predicted using GA for minimum overcut is listed in Trial Overcut
Table 4. number Pulse Peak Flushing (mg/min)
on current pressure
time (A)
Best: 0.0098289 Mean: 0.011419
(µs) (Kg/cm2)
0.4
minimum overcut (mm)
Best fitness
0.3 Mean fitness
1 18 0.7 0.1 0.0526562
2 18 0.7 0.1 0.0517556
0.2 3 12 0.7 0.2 0.0462829
4 12 1.2 0.2 0.0482794
0.1 5 12 1.2 0.3 0.0358922
6 5 1.2 0.3 0.0278363
0 7 5 1.2 0.4 0.0265262
0 5 10 15 8 1 1.7 0.4 0.0144687
Generation
9 1 1.7 0.5 0.0128623
Current Best Individual
10 1.5 1.9 0.5 0.0098289
2
control parameter values
1.5 3.2 Validity of GA predicted results
Validation of the simulation results with
1
the experimental results is done in order to conform
the simulation results to the actual working
0.5 conditions and to know how much is it varying with
the actual experimental results which is measured by
0 the percentage of prediction error.
1 2 3 The percentage of prediction error is calculated as
Independent control parameters Prediction error%
Experiment al result - GA predicted result
Fig. 2 GA predicted plot for minimum overcut and 100
the control parameter values Experiment al result
In order to validate the test results
predicted by GA, five random experimental results
are compared with the GA predicted results as
shown in Table 5.
Table 5 Comparison of Experimental and GA predicted results
Experimental result GA predicted result Prediction error %
Sl.no.
Tool wear rate overcut Tool wear rate overcut Tool wear rate overcut
1 0.00112 0.0665 0.00109 0.06483 2.678 2.511
2 0.00136 0.0503 0.00128 0.0542 5.882 7.195
3 0.00089 0.0321 0.00083 0.0315 6.741 1.869
4 0.00152 0.0195 0.00148 0.0191 2.631 2.051
5 0.00082 0.0402 0.0008263 0.0413 0.762 2.663
Average percentage of error 3.738 3.257
It is observed from the table that average prediction Multiobjective optimization problems are also found
percentage error is well within acceptable limits in machining processes. For nontrivial
thus establishing the results predicted using GA to multiobjective problems, such as minimizing tool
be valid. wear rate and minimizing overcut while drilling
microholes by microEDM on a Titanium alloy, it is
4. MULTI OBJECTIVE OPTIMIZATION difficult to identify a single solution that
Multi-objective optimization is the process simultaneously optimizes each objective. While
of simultaneously optimizing two or more searching for solutions, one reaches points where
conflicting objectives subject to certain constraints. upon an attempt to improve an objective further
deteriorates the second objectives. A tentative
1989 | P a g e
5. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
solution during such cases is called non-dominated, 4.1 Multiobjective Optimization using Genetic
Pareto optimal, if it cannot be eliminated by Algorithm
replacing it with another solution which improves an GA is run in MATLAB for generating
objective without worsening the other. The main Pareto optimal solution points for minimizing tool
objective when setting up and solving a wear rate and overcut while drilling micro holes by
multiobjective optimization problem is to find such micro EDM in Titanium super alloy. Equation for
non-dominated solutions. creating a fitness function for the multi objective
Friedrich et al [18] performed runtime optimization is written in a .M file. The range of the
analyses and observed that a fair Multi Objective process parameters is placed as bounds on the three
Evolutionary Algorithm has a marked preference for input control variables and the following algorithm
accepting quick small improvements. This helps to options are set.
find new solutions close to the current population Selection function : Tournament of
quicker. Different types of multi objective GA size 2
developed for specific purpose differ from each Crossover function : scattered
other mainly by using specialized fitness functions Mutation function : Adaptive
and introducing methods to promote solution feasible
diversity. An elitist multiobjective GA ensures that Direction of migration : Forward with migration
the best solution does not deteriorate in the function 0.2
succeeding generations. This approach uses a Distance measure function : distance
priority-based encoding scheme for population crowding
initialization. Population size : 75
Eiben and Smit [19] observed that adoption The variant of GA used to solve this
of parameter tuners would enable better multiobjective optimization problem is a controlled
evolutionary algorithm design. Using tuning elitist genetic algorithm (a variant of NSGA-II).
algorithms one can obtain superior parameter values Elitist GA favors individuals with better fitness
as well as information about problem instances, value. A controlled elitist GA maintains the
parameter values, and algorithm performance. This diversity of population for convergence to an
information can serve as empirical evidence to optimal Pareto front.
justify design decisions. Lianga and Leung [20] Weighted average change in the fitness
integrated GA with adaptive elitist-population function value over 150 generations is used as the
strategies for multimodal function optimization. criteria for stopping the algorithm. The optimized
Adaptive Elitist GA is shown to be very efficient pareto front achieved after 50 iterations is shown in
and effective in finding multiple solutions of Figure 1. Input control parameters corresponding to
complicated benchmark and real-world multimodal each of the pareto optimal set of solutions are
optimization problems. tabulated in Table 6 .
Zio and Bazzo [21] proposed a clustering
procedure for reducing the number of representative
solutions in the Pareto Front of multiobjective -3
x 10
optimization problems. The procedure is then 9.8
applied to a redundancy allocation problem. The Pareto front
results show that the reduction procedure makes it 9.7
easier for the decision maker to select the final
9.6
solution and allows him or her to discuss the
outcomes of the optimization process on the basis of 9.5
his or her assumed preferences. The clustering
Overcut (mm)
technique is shown to maintain the Pareto Front 9.4
shape and relevant characteristics. Su and Hou [22]
showed that the integrated multi population 9.3
intelligent GA approach can generate the Pareto-
optimal solutions for the decision maker to 9.2
determine the optimal parameters to assure a stable
9.1
process and product qualities in the nano-particle
milling process.
9
The chief advantage of GA when applied to
solve multi-objective optimization problems is the 8.9
computation of an approximation of the entire 7.8 8 8.2 8.4 8.6 8.8 9 9.2 9.4 9.6 9.8
tool wear rate (mg/min) -4
Pareto front in a single algorithm run. Thus, x 10
considering the advantages of GA for solving
multiobjective problems, it is applied to optimize Fig. 3 Pareto-optimal set of solutions obtained for
the process of microhole drilling by micro EDM. multi objective optimization
1990 | P a g e
6. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
From the table, it is observed that an
The two conflicting responses of minimizing tool improvement in minimizing tool wear rate
wear rate and overcut are marked along x-axis and deteriorates the quality of overcut and vice versa.
y-axis respectively as shown in Figure 3. The Thus, each solution point is a unique non dominated
individual star marks between these axes depict solution point.
individual non dominated solution point among the
pareto optimal set of all the star points which form Table 6 Process decision variables corresponding
the pareto front. The observed responses and the to each of the pareto optimal solution point
corresponding control parameter values are listed in and the predicted responses using GA
Table 6.
Sl Control parameters Responses
no. Pulse on time (µs) Peak current Flushing pressure Tool wear rate Overcut
(A) (Kg/cm2) (mg/min) (mm)
1 13.722 0.752 0.1 0.000786 0.00965
2 13.730 0.760 0.108 0.00079 0.0096
3 13.736 0.768 0.115 0.000798 0.00958
4 13.743 0.775 0.122 0.000799 0.00952
5 13.756 0.780 0.128 0.000804 0.0095
6 13.766 0.787 0.132 0.000805 0.00948
7 13.773 0.796 0.139 0.000806 0.00946
8 13.782 0.80 0.142 0.000816 0.00944
9 13.788 0.806 0.148 0.000817 0.00942
10 13.792 0.810 0.153 0.000821 0.0094
11 14.805 0.817 0.159 0.000823 0.00938
12 14.808 0.825 0.164 0.000826 0.00936
13 14.818 0.836 0.169 0.000827 0.00934
14 14.824 0.844 0.173 0.00083 0.0093
15 14.830 0.853 0.182 0.000836 0.00929
16 14.842 0.862 0.192 0.00084 0.00928
17 14.848 0.868 0.198 0.000844 0.00926
18 14.858 0.870 0.2 0.000846 0.00924
19 14.862 0.877 0.204 0.00085 0.0092
20 14.873 0.885 0.209 0.000856 0.00919
21 15.878 0.894 0.214 0.000859 0.00918
22 15.885 0.898 0.218 0.000861 0.00917
23 15.886 0.90 0.225 0.000862 0.00916
24 15.894 0.906 0.229 0.000869 0.00915
25 15.902 0.914 0.234 0.00087 0.0091
26 15.906 0.918 0.238 0.000881 0.00908
27 15.918 0.926 0.242 0.000884 0.00906
28 15.927 0.935 0.249 0.0009 0.00903
29 15.931 0.943 0.253 0.000901 0.00901
30 15.957 0.953 0.259 0.000924 0.00898
31 15.958 0.960 0.264 0.000932 0.00897
32 15.959 0.972 0.269 0.000944 0.00896
33 15.96 0.998 0.274 0.000954 0.00895
5. RESULT AND ANALYSIS corresponding control parameter values of 1µs for
While drilling micro holes by micro EDM pulse on time, 0.4 A for peak current and 0.1
in a Titanium (Ti-6Al-4V) super alloy, two kg/cm2. It is observed that the all three of the control
objectives, tool wear rate and overcut are considered parameters are to be set at low values in order to
to be important as they affect the machining obtain minimum tool wear rate.
efficiency and the quality of the product Similarly, the minimum overcut predicted
respectively. While optimizing the responses using GA is 0.00098289 mm with the corresponding
individually, the GA predicted value of minimum control parameter values of 1.5µs for pulse on time,
tool wear rate is 0.00082663 mg/min with the 1.9 A for peak current and 0.5 kg/cm2.. It is
observed that pulse on time is to be set at low value
1991 | P a g e
7. Ruben Phipon, B.B.Pradhan / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1986-1993
while the peak current and flushing pressure are to 6. CONCLUSION
be set at maximum values to obtain minimum Titanium super alloy has a wide range of
overcut. applications in engineering due to its characteristic
Also, the average percentage prediction of high strength to weight ratio. Micro EDM offers a
error of GA when compared with the experimental suitable process for drilling microholes in Titanium
results as shown in Table 5 is 3.738 % and 3.257% alloy mainly due to its characteristic of non contact
for tool wear rate and overcut respectively . Thus, between the tool and the work piece. The qualities
the GA predicted results are within acceptable limits required during micro hole drilling in Titanium alloy
establishing the validity of the GA as an appropriate is to decrease the tool wear rate and overcut while
optimization technique for the micro EDM process. drilling a microhole. The tool wear rate can be
The two objectives are conflicting in nature. This considered as a measure of machining efficiency
multi objective problem is then optimized using the and the overcut a measure of the quality of the hole
multiobjective GA in MATLAB software. The produced. Thus, it is a min-min two objective
solution obtained is a set of pareto optimal points as optimization problem. Also, the two objectives are
shown in Fig. 3 where each point is non dominated. conflicting in nature. Solution to such optimization
The observed responses were obtained in a single problems is best described by a set of pareto optimal
process parametric combination setting. Table 6 non dominated points as presented in this research
records the range of values for responses at different work . The decision maker is left with the choice of
parametric combination. It is observed that an trade off between these two objectives which further
increase in peak current increases the available increase the flexibility to select the optimal cutting
discharge energy, hence the tool wear rate also parameters.
increases. While the peak current decreases, the
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