This paper is published in Volume-4, Issue-5, 2018
Area
Mechanical Engineering
Author
Govind Prasad Patel, Ashish Parkhe
Org/Univ
NIIST Bhopal, Madhya Pradesh, India
Pub. Date
15 October, 2018
Paper ID
V4I5-1415
Publisher
Keywords
Fused deposition modeling, Rapid prototyping, Grey-Taguchi, Taguchi

Citationsacebook

IEEE
Govind Prasad Patel, Ashish Parkhe. Parameters optimization of fused deposition modelling process for the improvement of tensile strength using Taguchi based grey relational analysis, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Govind Prasad Patel, Ashish Parkhe (2018). Parameters optimization of fused deposition modelling process for the improvement of tensile strength using Taguchi based grey relational analysis. International Journal of Advance Research, Ideas and Innovations in Technology, 4(5) www.IJARIIT.com.

MLA
Govind Prasad Patel, Ashish Parkhe. "Parameters optimization of fused deposition modelling process for the improvement of tensile strength using Taguchi based grey relational analysis." International Journal of Advance Research, Ideas and Innovations in Technology 4.5 (2018). www.IJARIIT.com.

Abstract

FDM is an additive manufacturing method and the prototypes are made by layer by layer addition of semi-molten plastic material onto the platform from bottom to top. The design inspects the effect of the process parameters layer thickness, orientation and layer spacing that affects the tensile strength of the part produced by the Fused Deposition Modelling. Hence, the Optimization of these process parameters of FDM is able to make the system more specific and repeatable and such progression can guide to use of FDM in rapid manufacturing solicitations rather than only producing prototypes. The PLA material was used in this research work to build parts. The experimentation has been completed with the help of Taguchi L9 orthogonal array. Taguchi grey relational analysis is used to optimize the process parameters on multiple performance characteristics such as tensile strength. The proposed method enables decision analysts to better recognize the complete evaluation process and provide maximum tensile strength.