Abstract
Smart factory is the foundation of intelligent manufacturing. Intelligent devices are applied to monitor and adjust factory production process and optimize production performance. Aiming at the problem that traditional decision system in die casting factory ignores the value of manufacturing data, the data driven die casting smart factory solution is developed. The key technology of intelligent factory is reviewed, and a new “Data + Prediction + Decision Support” mode of operation analysis and decision system based on data driven is put forward. Combined with the key technology of die casting and the application of data driven new mode, the “Physics + Information + Decision” three layers of cyber-physical system is designed. This solution digs the value of manufacturing data, and promote the efficient production of die casting smart factory.
Supported by the project of 2016 Ministry of Industry and Information in the Intelligent Manufacturing: Application of new model of high silicon aluminum alloy engine cylinder block without cylinder 3000 tons high vacuum die casting intelligent workshop.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zuehlke, D.: Smart factory—towards a factory-of-things. J. Ann. Rev. Control 34(1), 129–138 (2010)
Sun: Commentary of the development trend for intelligent equipment manufacturing industry in the future. J. Process Autom. Instrum. 34(1), 1–5 (2013)
Zhu, H., Li, Y., Liu, K.: Smart factory architecture standard for middle and low-voltage switchgear assembly industry. J. Comput. Integr. Manufact. Syst. 23(6), 1216–1223 (2017)
Harrison, R., Vera, D., Ahmad, B.: Engineering the smart factory. J. Chin. J. Mech. Eng. 29(6), 1046–1051 (2016)
Zhong, R.Y., Xu, X., Wang, L.: IoT-enabled smart factory visibility and traceability using laser-scanners. J. Procedia Manufact. 10, 1–14 (2017)
Wang, S., Zhang, C., Liu, C., et al.: Cloud-assisted interaction and negotiation of industrial robots for the smart factory. J. Comput. Electr. Eng. 63, 66–78 (2017)
Lv, Zhang: Big-data-based technical framework of smart factory. J. Comput. Integr. Manufact. Syst. 22(11), 2691–2697 (2016)
Zhang, J., Gao, L., Qin, W.: Big-data-driven operational analysis and decision-making methodology in intelligent factory. J. Comput. Integr. Manufact. Syst. 22(5), 1220–1228 (2016)
Sun: Research on the key technology of the intelligent manufacturing system in die-casting workshop and system development. D. Zhejiang University (2017)
Xu: Research and development and architecture design of die-casting plant manufacturing system software. D. Zhejiang University (2017)
Laney, D.: 3D data management: controlling data volume, velocity and variety [EB/OL], 6 February 2001. https://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf. Accessed 15 Jun 2015
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhao, Y., Qian, F., Gao, Y. (2018). Data Driven Die Casting Smart Factory Solution. In: Wang, S., Price, M., Lim, M., Jin, Y., Luo, Y., Chen, R. (eds) Recent Advances in Intelligent Manufacturing . ICSEE IMIOT 2018 2018. Communications in Computer and Information Science, vol 923. Springer, Singapore. https://doi.org/10.1007/978-981-13-2396-6_2
Download citation
DOI: https://doi.org/10.1007/978-981-13-2396-6_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2395-9
Online ISBN: 978-981-13-2396-6
eBook Packages: Computer ScienceComputer Science (R0)