Real-time monitoring of silica ceramic composites grinding surface roughness based on signal spectrum analysis

Author(s):  
Yang Li ◽  
Yanhou Liu ◽  
Jinling Wang ◽  
Yi Wang ◽  
Yebing Tian
Author(s):  
Dazhong Wu ◽  
Yupeng Wei ◽  
Janis Terpenny

To realize high quality, additively manufactured parts, real-time process monitoring and advanced predictive modeling tools are crucial for accelerating quality assurance and quality control in additive manufacturing. While previous research has demonstrated the effectiveness of physics- and model-based diagnosis and prognosis for additive manufacturing, very little research has been reported on real-time monitoring and prediction of surface roughness in fused deposition modeling (FDM). This paper presents a new data-driven approach to surface roughness prediction in FDM. A real-time monitoring system is developed to monitor the health condition of a 3D printer and FDM processes using multiple sensors. A predictive model is built by random forests (RFs). Experimental results have shown that the predictive model is capable of predicting the surface roughness of a printed part with very high accuracy.


2006 ◽  
Vol 175 (4S) ◽  
pp. 521-521
Author(s):  
Motoaki Saito ◽  
Tomoharu Kono ◽  
Yukako Kinoshita ◽  
Itaru Satoh ◽  
Keisuke Satoh

2001 ◽  
Vol 11 (PR3) ◽  
pp. Pr3-1175-Pr3-1182 ◽  
Author(s):  
M. Losurdo ◽  
A. Grimaldi ◽  
M. Giangregorio ◽  
P. Capezzuto ◽  
G. Bruno

2014 ◽  
Author(s):  
Rozaimi Ghazali ◽  
◽  
Asiah Mohd Pilus ◽  
Wan Mohd Bukhari Wan Daud ◽  
Mohd Juzaila Abd Latif ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 101-LB
Author(s):  
ABHINAV BHUSHAN ◽  
SONALI J. KARNIK

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