kumoh national institute of technology
Networked Systems Lab.

Danielle Jaye S. Agron, Cosmas Ifeanyi Nwakanma, Jae-Min Lee and Dong-Seong Kim, "Smart Monitoring for SLA-type 3D Printer using Artificial Neural Network" 2020 Korean Institute of Communication and Sciences (KICS) Summer Conference, August 12-14, 2020, Yong Pyong Resort, Pyeongchang, Gangwon Province, Korea (N12)
By :
Date : 2020-07-20
Views : 97

In the additive manufacturing, a relatively high oxygen concentration inside a Stereolithography Apparatus (SLA-type) of three dimensional (3D)-printer during the operation have high risk of degrading the quality of the product. Monitoring such level of oxygen is still an open challenge to solve in the additive manufacturing industry. This paper presents a design of  a collaborative sensor system that monitors the normal oxygen level during the printing process. Furthermore, an artificial neural network(ANN) to predict the future values and prevent the oxygen concentration to reach the critical level was proposed. Results of the ANN performance is 96%. Since this is a preliminary result, future work be aimed at improving both data collection procedure and accuracy performance of the neural network to meet the real time requirements of 99.9999%