Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

Study on Hot Forming Parameters of Torsion Beam Based on Regression Analysis

Authors
Fei Xiong, Guiyong Yang, Tao Jiang, Kai Yu
Corresponding Author
Fei Xiong
Available Online January 2017.
DOI
10.2991/icmmita-16.2016.24How to use a DOI?
Keywords
Orthogonal test; Regression analysis; Martensite; Hot forming
Abstract

It is found the hot forming quality has close related to the initial temperature of the pressing die, the blank, pressing speed, cooling rate and the friction between the part and tools. Through the design of orthogonal test and multiple regression analysis, the regression model of thinning rate and these factors are obtained. The model has 99% significance and credibility. By the variance analysis of independent variables and dependent variables, the confidence level is 99.91%, and the residual analysis results show a good correlation between the measured values and the calculated values. The results show that the modified model has high reliability.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
10.2991/icmmita-16.2016.24
ISSN
2352-538X
DOI
10.2991/icmmita-16.2016.24How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Fei Xiong
AU  - Guiyong Yang
AU  - Tao Jiang
AU  - Kai Yu
PY  - 2017/01
DA  - 2017/01
TI  - Study on Hot Forming Parameters of Torsion Beam Based on Regression Analysis
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 121
EP  - 124
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.24
DO  - 10.2991/icmmita-16.2016.24
ID  - Xiong2017/01
ER  -