Predictive Modeling of Surface Roughness Based on Response Surface Methodology after WAAM

DOI

10.2991/ice2me-19.2019.11How to use a DOI?

Keywords

surface roughness predictive; parameters optimization; response surface methodology; WAAM

Abstract

A hybrid technique of additive manufacturing and subtractive process has provided a new solution combining product design and control by software. Wire Arc Additive Manufacturing (WAAM) process wins well-respected because of its low cost and high efficiency of deposition, nevertheless the process has its limitation of high heat input and low forming accuracy. A new process of additive manufacturing with high efficiency of modeling is urgent needed which can control heat transfer, mass transfer and force transfer. To overcome the disadvantage upon, various hybrid manufacturing techniques have been developed with high efficiency and controlled modeling in recently. The machining process in hybrid manufacturing has more different characteristics from traditional material removal processes, such as residual stress and heat in the blank. These influence the whole efficiency of the hybrid manufacturing. The essential task of this paper is to explore the feasibility of thermal machining during this process and make rational use of AM in order to obtain optimal accuracy.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hongyu Tian
AU  - Zhenyang Lu
AU  - Fang Li
AU  - Shujun Chen
PY  - 2019/03
DA  - 2019/03
TI  - Predictive Modeling of Surface Roughness Based on Response Surface Methodology after WAAM
BT  - Proceedings of the 2019 International Conference on Electronical, Mechanical and Materials Engineering (ICE2ME 2019)
PB  - Atlantis Press
SP  - 47
EP  - 50
SN  - 2352-5401
UR  - https://doi.org/10.2991/ice2me-19.2019.11
DO  - 10.2991/ice2me-19.2019.11
ID  - Tian2019/03
ER  -