Automated sampling decision scheme for the AVM system

Reducing the sampling rate to as low as possible is a high priority for many factories to reduce production cost. Automatic virtual metrology based intelligent sampling decision (ISD) scheme had been previously developed for reducing the sampling rate and sustaining the virtual metrology (VM) accura...

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Bibliographic Details
Published in:International journal of production research 2016-11, Vol.54 (21), p.6351-6366
Main Authors: Cheng, Fan-Tien, Hsieh, Yao-Sheng, Chen, Chun-Fang, Lyu, Jhao-Rong
Format: Article
Language:English
Subjects:
Accuracy
automated sampling decision (ASD)
automatic virtual metrology (AVM)
Automation
continuous improvement
Control charts
Industrial plants
intelligent sampling decision (ISD)
Metrology
Monitors
Real time
Sampling
Wastes
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Summary:Reducing the sampling rate to as low as possible is a high priority for many factories to reduce production cost. Automatic virtual metrology based intelligent sampling decision (ISD) scheme had been previously developed for reducing the sampling rate and sustaining the virtual metrology (VM) accuracy. However, the desired sampling rate of the ISD scheme is fixed and set manually. Hence, whenever the VM accuracy gets worse, it cannot adaptively increase the default sampling rate in the ISD scheme. As a consequence, it would take more time to collect enough samples for improving the VM accuracy. Moreover, when the VM accuracy performs well all the time, it cannot automatically decrease the default sampling rate in ISD, which may result in unnecessary waste. Accordingly, this paper proposes an automated sampling decision (ASD) scheme to adaptively and automatically modify the sampling rate online and in real time for continuous improvement. The ASD scheme can monitor the VM accuracy online as well as update the VM models in real time for maintaining the VM accuracy when the VM accuracy becomes poor. Also, the ASD scheme can automatically reduce the sampling rate while the VM accuracy performs well.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2015.1072649