Cloud 3D Printing Information Research

Authors

  • Yunlong He
  • Liang Guo

DOI:

https://doi.org/10.54097/b7yjyk73

Keywords:

Cloud 3D printing; Cloud manufacturing; Information model; Agent model.

Abstract

3D printing technology, as a major technological change in the global manufacturing industry, has gradually become the trend of The Times. As a service-oriented intelligent manufacturing system, cloud manufacturing has been widely studied by scholars at home and abroad in recent years. This paper takes cloud manufacturing as the carrier, studies the informatization of 3D printing service under cloud environment, elaborates the construction of 3D printing service information model in detail, and instantiates through Agent mapping model. This paper creates an implementation path for cloud 3D printing to provide on-demand precision manufacturing services.

Downloads

Download data is not yet available.

References

Zhou, L., et al., Multi-task scheduling of distributed 3D printing services in cloud manufacturing. The International Journal of Advanced Manufacturing Technology, 2018. 96(9-12): p. 3003-3017.

Ren, L., et al., Cloud manufacturing: key characteristics and applications. International journal of computer integrated manufacturing, 2017. 30(6): p. 501-515.

Lu, Y.Q. and X. Xu, Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2019. 57: p. 92-102.

Guo, L. and J. Qiu, Combination of cloud manufacturing and 3D printing: research progress and prospect. The International Journal of Advanced Manufacturing Technology, 2018. 96(5-8): p. 1929-1942.

Darwish, L.R., M.T. El-Wakad and M.M. Farag, Towards sustainable industry 4.0: A green real-time IIoT multitask scheduling architecture for distributed 3D printing services. Journal of Manufacturing Systems, 2021. 61: p. 196-209.

Xu, W.J., et al., Dynamic Modeling of Manufacturing Equipment Capability Using Condition Information in Cloud Manufacturing. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2015. 137(4).

Wu, Q., et al., Online order scheduling of multi 3D printing tasks based on the additive manufacturing cloud platform. Journal of Manufacturing Systems, 2022. 63: p. 23-34.

Mai, J.G., et al., Customized production based on distributed 3D printing services in cloud manufacturing. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016. 84(1-4): p. 71-83.

Abd, A.Y. and N. Piterman, Modelling and verification of reconfigurable multi-agent systems. Auton Agent Multi Agent Syst, 2021. 35(2): p. 47.

Canese, L., et al., Multi-Agent Reinforcement Learning: A Review of Challenges and Applications. Applied Sciences, 2021. 11(11): p. 4948.

Wang, X., et al., Dynamic scheduling of tasks in cloud manufacturing with multi-agent reinforcement learning. Journal of Manufacturing Systems, 2022. 65: p. 130-145.

Gronauer, S. and K. Diepold, Multi-agent deep reinforcement learning: a survey. The Artificial intelligence review, 2022. 55(2): p. 895-943.

Downloads

Published

12-03-2024

Issue

Section

Articles

How to Cite

He, Y., & Guo, L. (2024). Cloud 3D Printing Information Research. Academic Journal of Science and Technology, 9(3), 258-262. https://doi.org/10.54097/b7yjyk73