The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Machine Learning Approach of Bio Silica Suspended Dielectric in EDM of Ti6Al4V for Biomedical Application
|
|
Author(s): B. Yokesh Kumar (Chennai Institute of Technology, India), S. Baskar (Centre for Nonlinear Systems, Chennai Institute of Technology, India), N. Pragadish (Department of Mechatronics Engineering, Chennai Institute of Technology, India)and A. Thenmozhi (Kings Engineering College, India)
Copyright: 2023
Pages: 18
Source title:
Handbook of Research on Advanced Functional Materials for Orthopedic Applications
Source Author(s)/Editor(s): R. Ranjith (SNS College of Technology, India)and J. Paulo Davim (University of Aveiro, Portugal)
DOI: 10.4018/978-1-6684-7412-9.ch010
Purchase
|
Abstract
A machine learning technique, the artificial neural network is used to predict the output responses of Ti6Al4V in electrical discharge machining, using nano bio silica infused vegetable oil methyl ester dielectric fluid and optimizing the operating parameters of electrical discharge machining by using the Jaya algorithm. The input parameters of the experiments are peak current, pulse on time, discharge voltage, and duty cycle, and the measured output responses are the material removal rate, tool wear rate, and surface roughness. The optimal architecture of the artificial neural network model is recognized as 4-10-10-3. The correlation coefficient of the artificial neural network prediction is 0.9626, and the least mean absolute percentage error of the material removal rate, tool wear rate, and surface roughness are 0.8129, 0.3337, and 1.2595%, respectively. The artificial neural network predicted accurate results and the Jaya algorithm optimized the operating parameters of Ti6Al4V in electrical discharge machining.
Related Content
|
Dipan Kumar Das, Padmaja Patnaik, Sudip Kumar Das, Nibedita Nayak.
© 2026.
28 pages.
|
|
Aditya Shrivastav, Sunil Sankathala, Kashvi Chaturvedi, Susanta Das.
© 2026.
18 pages.
|
|
Amruta Prasann Walvekar, Rutuja Vijay Kamble, Tejal Nikhil Bele, Pallavi Singh Chouhan, Shraddha Devarshi.
© 2026.
44 pages.
|
|
Pallavi Singh Chouhan, Amruta Prasann Walvekar, Shraddha Prakash Devarshi, Tejal Nikhil Bele, Rutuja Vijay Kamble.
© 2026.
32 pages.
|
|
M Amin Mir, Eskilla Venkata Ramana, Syed M. Hasnain, Maythem Mahmoud, Kim Andrews.
© 2026.
24 pages.
|
|
Muhammad Waqar Ashraf, Mohammad Amin Mir, Syed M. Hasnain, Kim Andrews.
© 2026.
30 pages.
|
|
Harshit Gouri.
© 2026.
30 pages.
|
|
|