Affiliation:
1. Jinggangshan University
Abstract
A remote network monitoring model for large-scale materials manufacturing is proposed, including five modules: center control module, data collection and fault alarm module, graph drawing module and data storage module. The center control module not only interacts with users, but also controls the other four modules to work together in harmony. According to this monitoring model, a remote network monitoring platform is designed and realized. The user can interact with the control center module through an Internet browser, and the information about the monitored manufacturing machines and devices can be displayed by means of text, chart, graphic and sound, etc. Moreover, the details about the problems or faults from the monitored objects can be obtained in time. The experimental results indicate that the network monitoring platform can accurately get the information of the monitored objects, and users can conveniently get the online running state of those monitored objects.
Publisher
Trans Tech Publications, Ltd.
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science
Reference11 articles.
1. BERNHARD SICK: On-line and indirect tool wear monitoring in turning with artificial neural networks: A review of more than a decade of research; In: Mechanical Systems and Signal Processing, 16(2002), pp.487-546.
2. H. -P. Wiendahla and S. Lutza: Production in Networks; In: Manufacturing Technology, 51(2002), pp.573-586.
3. Ralph Steiner, Michael Schneider, Felix Mayer: Current monitor system and a method for manufacturing it; U.S. Patent 6, 356, 068. (2002).
4. Bond, L. Sutton, D. Turnquest: Use of multiple lithography monitors in a defect control strategy for high volume manufacturing; In: Advanced Semiconductor Manufacturing Conference and Workshop, 9(1999).
5. Zhiqiang Ge, Zhihuan Song: Semiconductor Manufacturing Process Monitoring Based on Adaptive Substatistical PCA; In: IEEE Transactions on Semiconductor Manufacturing, 23 (2010), pp.99-108.