EOS completes pilot phase for 3D printing process monitoring system

2016 ◽  
Vol 71 (6) ◽  
pp. 471
2019 ◽  
Vol 56 (4) ◽  
pp. 801-811
Author(s):  
Mircea Dorin Vasilescu

This work are made for determine the possibility of generating the specific parts of a threaded assembly. If aspects of CAD generating specific elements was analysed over time in several works, the technological aspects of making components by printing processes 3D through optical polymerization process is less studied. Generating the threaded appeared as a necessity for the reconditioning technology or made components of the processing machines. To determine the technological aspects of 3D printing are arranged to achieve specific factors of the technological process, but also from the specific elements of a trapezoidal thread or spiral for translate granular material in supply process are determined experimentally. In the first part analyses the constructive generation process of a spiral element. In the second part are identified the specific aspects that can generation influence on the process of realization by 3D DLP printing of the two studied elements. The third part is affected to printing and determining the dimensions of the analysed components. We will determine the specific value that can influence the process of making them in rapport with printing process. The last part is affected by the conclusions. It can be noticed that both the orientation and the precision of generating solid models have a great influence on the made parts.


2021 ◽  
pp. 50965
Author(s):  
Kankavee Sukthavorn ◽  
Natkritta Phengphon ◽  
Nollapan Nootsuwan ◽  
Pongsakorn Jantaratana ◽  
Chatchai Veranitisagul ◽  
...  

2011 ◽  
Vol 291-294 ◽  
pp. 3036-3043 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Channarong Rungruang

The aim of this research is to propose and develop the in-process monitoring system of the tool wear for the carbon steel (S45C) in CNC turning process by utilizing the multi-sensor which are the force sensor, the sound sensor, the accelerometer sensor and the acoustic emission sensor. The progress of the tool wear results in the larger cutting force, the higher amplitude of the acceleration signal, and the higher power spectrum densities of sound and acoustic emission signals. Hence, their signals have been integrated via the neural network with the back propagation technique to monitor the tool wear. The experimentally obtained results showed that the in-process monitoring system proposed and developed in this research can be effectively used to estimate the tool wear level with the higher accuracy and reliability.


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