학술논문

Optimization of electric discharge machining process parameters using carbon nanotubes
Document Type
Conference
Source
2017 International Conference on Nascent Technologies in Engineering (ICNTE) Nascent Technologies in Engineering (ICNTE), 2017 International Conference on. :1-6 Jan, 2017
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Machining
Rough surfaces
Surface roughness
Surface treatment
Electrodes
Signal to noise ratio
Discharges (electric)
Electric Discharge Machining
Material removal rate
Surface roughnes
Multi Walled Carbon nanotube (MWCNT)
Grey Relational Analysis
Language
Abstract
Manufacturing of quality products at lower cost is the essential need for industries to arrive at the best manufacturing conditions, which can be obtained by using optimization techniques. In the present study, set of process parameters to be optimized are gap voltage, current, pulse ON time and multi walled carbon nanotube powder concentration in dielectric used in Electrical Discharge Machining (EDM) process. These parameters are investigated to identify the variations the performance characteristics of material removal rate and surface roughness. The material used for machining NAK80 Steel is a copper electrode. Based on the four factors at three levels, Taguchi's L9 orthogonal array is selected for carrying out the experiments. The objective of the present study is to get higher rate of material removal and lower surface roughness. The optimal solution is obtained by using Taguchi's Grey Relational Analysis method. MINITAB software was used to find the optimal levels of parameters in EDM process. The optimum result obtained was tested by carrying out the confirmation experiment. Based on the confirmation test, the improvements in material removal rate and surface roughness were 25% and 6.87% respectively. It is found from the present study that Taguchi's Grey relational Analysis is an effective technique to optimize the process parameters for Electric Discharge Machining.