A reconfigurable stamping die and its stamping process

2010 ◽  
Vol 15 (3) ◽  
pp. 313-318 ◽  
Author(s):  
Ai-ping Song ◽  
Wei-wei Wu ◽  
Jun Zhang
2010 ◽  
Vol 142 ◽  
pp. 107-111
Author(s):  
Bai Liu

Based on Finite Element Analysis (FEA) module of Dynaform software, the paper made numerical simulation of a wheel hub’s stamping process in the method of elastic-plastic flow, pointed out the behavior of deformation of stamping process, predicted and prevented stamping defect such as crack in the process, and calculated the degree of resilience. Consequently three forming numerical simulation schemes have been designed respectively, more feasible process parameters has been achieved in comparison with the features of each scheme.


2020 ◽  
Vol 15 ◽  
Author(s):  
Fei Sun ◽  
Guohe Li ◽  
Qi Zhang ◽  
Meng Liu

: Cr12MoV hardened steel is widely used in the manufacturing of stamping die because of its high strength, high hardness, and good wear resistance. As a kind of mainstream cutting technology, high-speed machining has been applied in the machining of Cr12MoV hardened steel. Based on the review of a large number of literature, the development of high-speed machining of Cr12MoV hardened steel was summarized, including the research status of the saw-tooth chip, cutting force, cutting temperature, tool wear, machined surface quality, and parameters optimization. The problems that exist in the current research were discussed and the directions of future research were pointed out. It can promote the development of high-speed machining of Cr12MoV hardened steel.


Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 262
Author(s):  
Chih-Yung Huang ◽  
Zaky Dzulfikri

Stamping is one of the most widely used processes in the sheet metalworking industry. Because of the increasing demand for a faster process, ensuring that the stamping process is conducted without compromising quality is crucial. The tool used in the stamping process is crucial to the efficiency of the process; therefore, effective monitoring of the tool health condition is essential for detecting stamping defects. In this study, vibration measurement was used to monitor the stamping process and tool health. A system was developed for capturing signals in the stamping process, and each stamping cycle was selected through template matching. A one-dimensional (1D) convolutional neural network (CNN) was developed to classify the tool wear condition. The results revealed that the 1D CNN architecture a yielded a high accuracy (>99%) and fast adaptability among different models.


2021 ◽  
Author(s):  
Pengcheng Wu ◽  
Zhenwei Wang ◽  
Xinhua Yao ◽  
Jianzhong Fu ◽  
Yong He

A recyclable, self-healing conductive nanoclay and corresponding stamping process are developed for printing flexible electronics directly and quickly in situ.


2018 ◽  
Vol 15 ◽  
pp. 427-435 ◽  
Author(s):  
Shiva Shankar Mangalore Babu ◽  
Stuart Berry ◽  
Michael Ward ◽  
Michal Krzyzanowski

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