TY - JOUR
T1 - Development of a private cloud-based new-generation virtual metrology system
AU - Hung, Min Hsiung
AU - Lin, Yu Chuan
AU - Huang, Hsien Cheng
AU - Tu, Chia Chun
AU - Cheng, Fan Tien
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Automatic virtual metrology (AVM) is the highest-level technology for VM applications from the perspective of automation. The existing PC-server-based AVM systems suffer several limitations, such as being incapable of parallel processing, having no high-Availability and fault-tolerance consideration, etc. The new model of IT usage and advantage offered by the emerging cloud computing can bring commercial benefits to industries. In this paper, we based on private cloud architecture and virtualization technology to develop a novel cloud-based AVM system for overcoming the shortcomings of the existing AVM system. Integrated test results in a case study applying the AVM system to perform VM tasks for semiconductor equipment show that the proposed cloud-based AVM system could demonstrate a significant performance improvement over the existing PC-based AVM system, while achieving the similar prediction accuracy. This paper can be a useful reference for industrial practitioners to construct cloud-based equipment monitoring systems.
AB - Automatic virtual metrology (AVM) is the highest-level technology for VM applications from the perspective of automation. The existing PC-server-based AVM systems suffer several limitations, such as being incapable of parallel processing, having no high-Availability and fault-tolerance consideration, etc. The new model of IT usage and advantage offered by the emerging cloud computing can bring commercial benefits to industries. In this paper, we based on private cloud architecture and virtualization technology to develop a novel cloud-based AVM system for overcoming the shortcomings of the existing AVM system. Integrated test results in a case study applying the AVM system to perform VM tasks for semiconductor equipment show that the proposed cloud-based AVM system could demonstrate a significant performance improvement over the existing PC-based AVM system, while achieving the similar prediction accuracy. This paper can be a useful reference for industrial practitioners to construct cloud-based equipment monitoring systems.
UR - http://www.scopus.com/inward/record.url?scp=84939599398&partnerID=8YFLogxK
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U2 - 10.1109/CoASE.2014.6899434
DO - 10.1109/CoASE.2014.6899434
M3 - Conference article
AN - SCOPUS:84939599398
SN - 2161-8070
VL - 2014-January
SP - 910
EP - 915
JO - IEEE International Conference on Automation Science and Engineering
JF - IEEE International Conference on Automation Science and Engineering
M1 - 6899434
T2 - 2014 IEEE International Conference on Automation Science and Engineering, CASE 2014
Y2 - 18 August 2014 through 22 August 2014
ER -