Machine learning-based model for detecting uneven wear and temperature deviation events in hot forging process

Author(s):  
Tsung-Liang Wu ◽  
Yu-Chun Hwang ◽  
Wei-Xun Zhang
2020 ◽  
Vol 107 (1-2) ◽  
pp. 39-47
Author(s):  
Luana De Lucca de Costa ◽  
Alberto Moreira Guerreiro Brito ◽  
André Rosiak ◽  
Lirio Schaeffer

2014 ◽  
Vol 81 ◽  
pp. 480-485 ◽  
Author(s):  
Takefumi Arikawa ◽  
Daisuke Yamabe ◽  
Hideki Kakimoto

2012 ◽  
pp. 625-631
Author(s):  
Michael Stoschka ◽  
Martin Stockinger ◽  
Hermann Maderbacher ◽  
Martin Riedler

Author(s):  
Panuwat Soranansri ◽  
Tanaporn Rojhirunsakool ◽  
Narongsak Nithipratheep ◽  
Chackapan Ngaouwnthong ◽  
Kraisuk Boonpradit ◽  
...  

In hot forging industry, the process design and the billet size determination are very crucial steps because those steps directly influence both the product quality and material utilization. The purpose of this paper was to propose a technique used to design the hot forging process for the manufacturing of the talar body prosthesis. The talar body prosthesis is one of the artificial bones, which its geometry is a free form shape. In this study, the Finite Element Modeling (FEM) was used as a tool to verify the proposed design before implementation in a production line. In addition, an initial billet was determined the optimum size in the FEM by varying the mass ratio factor, the diameter, and the length. It was found that the mass ratio factor is a very useful guideline since the optimum size is quite close to the provided size from the guideline. The FEM results showed that the dimensions of the initial billet significantly affect the complete metal filling in the die cavity. Moreover, the optimum size between the diameter and length can reduce the material waste in the hot forging process of the talar body prosthesis. Finally, the experimental results of the hot forging process showed that the proposed process design with the optimum size of the initial billet is achieved in order to manufacture the talar body prosthesis and the material utilization of the new proposed process is improved from the traditional process by 2.6 times.


2020 ◽  
Vol 9 (6) ◽  
pp. 13575-13593
Author(s):  
Xiaomin Huang ◽  
Baoyu Wang ◽  
Yong Zang ◽  
Hongchao Ji ◽  
Ben Guan ◽  
...  

2013 ◽  
Author(s):  
Shi-Hong Zhang ◽  
Hai-Yan Zhang ◽  
Hong-Wu Song ◽  
Ming Cheng

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