Article Fingerprint
ReserarchID
WSVEW
The development of new materials show the immense growth but the major problem, it is very difficult to machine the newly developed materials. So it is necessary to adopt some new machining methods. Electrical Discharge Machining (EDM) is a non-traditional and most popular machining method to manufacture dies, punches and press tools because of its capability to produce complicated, intricate shapes and to machine hard materials. From the industrial point of view stainless steel 316 is a very commonly used material due to its property of resistant to corrosion. During experimentation, electrode material, current and pulseon time were taken as variables for the study of material removal rate and surface roughness. Three different electrode materials copper, brass and graphite were used with EDM oil as a dielectric fluid in the experiment. Using Taguchi method, L9 orthogonal array has been chosen and three levels corresponding to each of the variables are taken. Experiments have been performed as per the set of experiments designed in the orthogonal array. Results of experimentation were analyzed analytically as well as graphically. Signal to Noise ratio was calculated to analyze the effect of input parameter more accurately. It is found that ANOVA has unable to find the key significant parameters for the output response due to less number of variables and factors. The optimal value of MRR and SR were also calculated using their signal to noise ratio value.
Dr. Krishan Kant. 2013. \u201cAnalysis of MRR and SR with different electrode for SS 316 on Die-Sinking EDM using Taguchi Technique\u201d. Global Journal of Research in Engineering - A : Mechanical & Mechanics GJRE-A Volume 13 (GJRE Volume 13 Issue A3): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
Total Score: 103
Country: India
Subject: Global Journal of Research in Engineering - A : Mechanical & Mechanics
Authors: Suraj Choudhary, Krishan Kant, Parveen Saini (PhD/Dr. count: 0)
View Count (all-time): 160
Total Views (Real + Logic): 4736
Total Downloads (simulated): 2411
Publish Date: 2013 05, Mon
Monthly Totals (Real + Logic):
This paper attempted to assess the attitudes of students in
Advances in technology have created the potential for a new
Inclusion has become a priority on the global educational agenda,
The development of new materials show the immense growth but the major problem, it is very difficult to machine the newly developed materials. So it is necessary to adopt some new machining methods. Electrical Discharge Machining (EDM) is a non-traditional and most popular machining method to manufacture dies, punches and press tools because of its capability to produce complicated, intricate shapes and to machine hard materials. From the industrial point of view stainless steel 316 is a very commonly used material due to its property of resistant to corrosion. During experimentation, electrode material, current and pulseon time were taken as variables for the study of material removal rate and surface roughness. Three different electrode materials copper, brass and graphite were used with EDM oil as a dielectric fluid in the experiment. Using Taguchi method, L9 orthogonal array has been chosen and three levels corresponding to each of the variables are taken. Experiments have been performed as per the set of experiments designed in the orthogonal array. Results of experimentation were analyzed analytically as well as graphically. Signal to Noise ratio was calculated to analyze the effect of input parameter more accurately. It is found that ANOVA has unable to find the key significant parameters for the output response due to less number of variables and factors. The optimal value of MRR and SR were also calculated using their signal to noise ratio value.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.