The Realization of Equipment Status Monitoring System Driven by Task Stage

Abstract:

The equipment resource planning is considered during the procedure of job schedules in manufacturing enterprises. Based on the analysis of interaction between production task and equipment status, a task driven equipment status monitoring system is presented. Through the development of an analyzer, the system can regulate the equipment status automatically according to the perform stage of production tasks and provide the adequate equipment information for job schedules. Finally, the application examples are introduced and the characteristics of the system are summarized as well.

• Periodical: Applied Mechanics and Materials (Volumes 333-335)
• Pages: 1695-1698
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.333-335.1695
• Online since: July 2013
• Authors: Xu Feng Tong, Dong Xia Zhang, Ru Han Baoa
• Keywords: Equipment Status, Monitoring System, Schedule

References

[1] Xiaodong Yao, Micheal Fu, Steven I. Marcus. Optimal preventive maintenance scheduling in semiconductor manufacturing[J]. IEEE Transactions on Semiconductor Manufacturing, 2004, 17(3):345-355

DOI: 10.1109/tsm.2004.831948

[2] A. Crespo Marquez, J.N.D. Gupta, J.P. Ignizio. Improving preventive maintenance scheduling in semiconductor fabrication facilities[J]. Production Planning and Control, 2006, 17(7):742-754

DOI: 10.1080/09537280600901525

[3] D. Daniel Sheu, Jun Yuan Kuo. A model for preventive maintenance operations and forecasting[J]. Journal of Intelligent Manufacturing, 2006, 17(4):441-451

DOI: 10.1007/s10845-005-0017-6

[4] Anne-Sylvie Charles, Ioana-Ruxandra Floru, Catherine Azzaro-Pantel, et al. Optimization of preventive maintenance strategies in a multipurpose batch plant: Application to semiconductor manufacturing[J]. Computers and Chemical Engineering, 2003, 27(4):449-467

DOI: 10.1016/s0098-1354(02)00216-8

[5] Argon Chen, R.S. Guo, G.S. Wu. Real-time equipment health evaluation and dynamic preventive maintenance. Proceedings of ISSM 2000, 2000:375-378

[6] Jing Qiu, Cheng Zhang, Brij B. Seth, et al. Damage mechanics approach for bearing lifetime prognostics[J]. Mechanical Systems and Signal Processing, 2002, 16 (5):817-829

DOI: 10.1006/mssp.2002.1483

[7] Asok Ray, Sekhar Tangirala. Stochastic modeling of fatigue crack dynamics for on-line failure prognostics[J]. IEEE Transactions on Control Systems Technology, 1996, 4 (4):443 – 451

DOI: 10.1109/87.508893