DocumentCode :
1587291
Title :
Visualizing the Yield Pattern Outcome for Automatic Data Exploration
Author :
Noor, Megat Norulazmi Megat Mohamed ; Jusoh, Shaidah
Author_Institution :
Grad. Dept of Comput. Sci., Univ. Utara Malaysia, Sintok
fYear :
2008
Firstpage :
404
Lastpage :
409
Abstract :
Non close loop manufacturing process, typically in the hard disk media industries rely from its inspection machine to generate production yield temporal data that can be used for future analysis. In order for an engineer to proactively perform maintenance on its process equipment and avoiding unnecessary unplanned down time, they need to be able to predict the outcome of the yield before products arrives at the inspection machine. The future prediction of the yield outcome can be achieved by visualizing the historical data pattern generated from the inspection machine, transform the data pattern and map it into machine learning algorithm for training in order to automatically generate a prediction model without the visual interpretation needs to be done by human.
Keywords :
data visualisation; inspection; learning (artificial intelligence); maintenance engineering; pattern classification; production engineering computing; automatic data exploration; inspection machine; lazy machine learning algorithm classifier; maintenance engineering; manufacturing yield pattern outcome visualization; nonclose loop manufacturing process; Data engineering; Data mining; Data visualization; Humans; Inspection; Maintenance; Manufacturing industries; Manufacturing processes; Production; Space technology; Automatic data exploration; Data mining; data visualization; machine learning; manufactuirng yield predictive system; predictive system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modeling & Simulation, 2008. AICMS 08. Second Asia International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-0-7695-3136-6
Electronic_ISBN :
978-0-7695-3136-6
Type :
conf
DOI :
10.1109/AMS.2008.26
Filename :
4530510
Link To Document :
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