TAILIEUCHUNG - Experimental study of distribution of energy during EDM process for utilization in thermal models

(BQ) In this study experiments have been performed to study the percentage fraction of energy transferred to the workpiece utilizing heat transfer equations, at different EDM parameters. This study also relates the optimum parameters with the optimum utilization of input discharge energy and hence will help to improve the technological performance of this process. | International Journal of Heat and Mass Transfer 55 (2012) 5053–5064 Contents lists available at SciVerse ScienceDirect International Journal of Heat and Mass Transfer journal homepage: Experimental study of distribution of energy during EDM process for utilization in thermal models Harminder Singh ⇑ Guru Nanak Dev University, Regional Campus, Jalandhar, Punjab 144 007, India a r t i c l e i n f o Article history: Received 3 September 2010 Received in revised form 25 April 2012 Accepted 27 April 2012 Available online 1 June 2012 Keywords: Energy distribution Sinking electro discharge machining EDM Mathematical model a b s t r a c t Electrical discharge machining (EDM) has steadily gained importance over the years because of its ability to cut and shape a wide variety of materials and complicated shapes with high accuracy. The effectiveness of the EDM process is evaluated in terms of the material removal rate, relative wear ratio and the surface roughness of the work piece. The input discharge energy during this process is distributed to various components of the process, which further influences the material removal rate and other machining characteristics like surface roughness. Since during this process the electrical energy is converted into heat energy, hence the theoretical modeling of this process is based upon the heat transfer equations and in all existing thermal models the fraction of the energy transferred to the workpiece, is one of the important parameters. The accurate prediction of the fraction of energy effectively transferred to the workpiece will help to reduce the errors of the thermal models. In this study experiments have been performed to study the percentage fraction of energy transferred to the workpiece utilizing heat transfer equations, at different EDM parameters. This study also relates the optimum parameters with the optimum utilization of input discharge energy and hence will help to improve the .

• Cơ khí - Chế tạo máy
• Electrical discharge machining
• The EDM process
• Energy distribution
• Sinking electro discharge machining
• Mathematical model
• Understanding electrical discharge machining
• Various Electric Discharge Machines
• Keeping Abreast With EDM Technology
• The Machining Revolution
• A strip electrode
• The machining principle
• Surface modification
• Powder metallurgy electrodes
• Surface finish
• Electrode wear
• Inconel 718
• Response Surface Methodology
• Multi Objective Particle SwarmOptimization
• The electrical discharge machining
• The EDM processes
• Process parameters
• Stainless steel
• Optimization of machining parameters
• Fuzzy logic analysis
• Analysis of variance
• Machining precision and accuracy
• Green manufacturing
• Multi attribute decision making
• Fuzzy TOPSIS methods
• Silicon carbide
• Die sinking EDM
• Ceramic composite
• Artificial neural network
• Multi objective optimization
• Genetic algorithm
• Orthogonal array
• Statistical analyses
• Decision making model for green EDM
• Electro Discharge Machining
• Material Removal Rate
• Polynomial model
• Neuro fuzzy model
• Non conventional machining
• Journal of Science and Technology
• Analysis of surface layers of hot
• Analysis of surface layers of hot – forging die
• Hot forging die following die sinking
• Taguchi methods
• Ideal function
• Ultrasonic vibration
• Dry EDM
• Powder additives
• EDM in water
• Multi response optimization
• Powder mixed electrical discharge machining
• Surface micro hardness
• Pulse on time
• Pulse off time
• Tool steel
• Surface roughness
• Examination of machining parameters
• EDM of tool steel
• Metal matrix composite
• Temperature stability
• Duty factor
• Titanium alloys
• Electrical process parameters
• State of art in EDM process
• Process parameters of wire cut
• 90CrSi tool steel
• Wire cut EDM
• Tool steel machining
• AISI P20 tool steel
• Fuzzy TOPSIS
• Sensitivity analysis
• The effect of multiple discharges
• Thermal model
• Roughness prediction
• Predictive model
• Discrimination of discharging pulses
• System identification