An online tool life prediction system for CNC turning using computer vision techniques

Author(s):  
P.J. Bagga ◽  
K.S. Bajaj ◽  
M.A. Makhesana ◽  
K.M. Patel
2010 ◽  
Vol 458 ◽  
pp. 355-361 ◽  
Author(s):  
Song Lin Ding ◽  
R. Izamshah R.A. ◽  
John Mo ◽  
Quan Sheng Liu

In order to reduce the risk of expensive tool failure in the machining of Titanium alloys, the paper presents a tool life prediction approach based on the analysis of cutting forces. Regression analysis was applied to develop the prediction model. Detailed steps of implementation are presented. Prediction logics and criteria are introduced. Cutting tests were carried out to validate the reliability of the proposed method. When compared with empirical methods the proposed approach which is based on the analysis of cutting force measured in the machining process appears far more effective in predicting tool life.


2019 ◽  
Vol 103 (9-12) ◽  
pp. 4627-4634 ◽  
Author(s):  
Hua An ◽  
Guofeng Wang ◽  
Yi Dong ◽  
Kai Yang ◽  
Lingling Sang

2011 ◽  
Vol 346 ◽  
pp. 527-532
Author(s):  
Wen Lun Cao ◽  
Bei Chen ◽  
Yu Yao He

The data acquisition and life prediction system of gas laser is designed in this paper. The ARM STM3210B module is used as the core of hardware platform. The software platform is composed of parameter setting module, measurement modules of threshold current and optimum operating current, life test module, life analysis and prediction module, reanalysis module of report form and historical data. This article expounds emphatically the relationships among different modules. Meanwhile, the design idea of data exchanges among system software, analysis algorithm and hardware drive is realized successfully.


2014 ◽  
Vol 105 ◽  
pp. 218-236 ◽  
Author(s):  
Han Liu ◽  
Mingyong Zhou ◽  
Yuli Zhou ◽  
Shan Wang ◽  
Guangxian Li ◽  
...  

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