Application of Deep Learning for Design Optimization in Additive Manufacturing Process
Author(s):
Eakansh Mahto, Dharmendra Tyagi
Keywords:
Additive Manufacturing, machine learning, Topology Optimization, Compliance, Density Distribution.
Abstract
Additive Manufacturing (AM) is an advanced fabrication technique that uses computerised three dimensional design information to construct components by accumulating textures chronologically. Due to “ their achievement in constructing complex and difficult design concepts, rapid prototype testing, and reduced-volume or one-of-a-kind manufacturing throughout many industry sectors, AM methodologies are becoming much more popular comparison to traditional initiatives. Computational simulations are indeed an important part of AM design and optimization because they completely remove costly manufacturing process trial and error. This motivates the development of a predictive tool based on machine learning (ML) that can produce simulation results instantly rather than requiring expensive physics-based simulations.
Article Details
Unique Paper ID: 154595

Publication Volume & Issue: Volume 8, Issue 11

Page(s): 842 - 850
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Go To Issue



Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies