TY - GEN
T1 - IoT-Based Real-Time 3D Printing Monitoring System
AU - Kazhymurat, Temirlan
AU - Shehab, Essam
AU - Ali, Md Hazrat
N1 - Funding Information:
The authors express their sincere gratitude to Nazarbayev University for financial support. This research is funded by Nazarbayev University, grant numbers 021220FD1551 and 11022021FD2904.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper presents IoT based real-time monitoring system for 3D printing. However, additive manufacturing or 3D printing allows complex solutions and innovations due to its superior advantages over conventional material removal processes. Monitoring and quality control of the printing process are still challenging to implement. There is a need for research efforts in creating IoT-based monitoring, control systems, smart manufacturing systems, and digital twin for the additive manufacturing process. The paper provides a real-time monitoring system for 3D printing based on the data receiving an approach from different embedded sensors in a real-time regime. The sensors are composed of thermocouples, accelerometers, thermistors, and cameras. Matlab-Arduino support package tools were employed for visualization data from sensors. The advantages of our proposed monitoring system are the simplicity of design and the availability of embedded sensors which can track actual data from the 3D printer machine and interface it through remote monitoring systems.
AB - This paper presents IoT based real-time monitoring system for 3D printing. However, additive manufacturing or 3D printing allows complex solutions and innovations due to its superior advantages over conventional material removal processes. Monitoring and quality control of the printing process are still challenging to implement. There is a need for research efforts in creating IoT-based monitoring, control systems, smart manufacturing systems, and digital twin for the additive manufacturing process. The paper provides a real-time monitoring system for 3D printing based on the data receiving an approach from different embedded sensors in a real-time regime. The sensors are composed of thermocouples, accelerometers, thermistors, and cameras. Matlab-Arduino support package tools were employed for visualization data from sensors. The advantages of our proposed monitoring system are the simplicity of design and the availability of embedded sensors which can track actual data from the 3D printer machine and interface it through remote monitoring systems.
KW - Additive manufacturing
KW - digital twin
KW - Fused Deposition Modelling
KW - in-situ monitoring
KW - Industry 4.0
KW - internet of things
UR - http://www.scopus.com/inward/record.url?scp=85143399609&partnerID=8YFLogxK
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U2 - 10.1109/SIST54437.2022.9945778
DO - 10.1109/SIST54437.2022.9945778
M3 - Conference contribution
AN - SCOPUS:85143399609
T3 - SIST 2022 - 2022 International Conference on Smart Information Systems and Technologies, Proceedings
BT - SIST 2022 - 2022 International Conference on Smart Information Systems and Technologies, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Smart Information Systems and Technologies, SIST 2022
Y2 - 28 April 2022 through 30 April 2022
ER -