DocumentCode
137492
Title
Classification algorithms for virtual metrology
Author
Tilouche, Shaima ; Bassetto, Samuel ; Nia, Vahid Partovi
Author_Institution
Dept. of Math. & Ind. Eng., Ecole Polytech. de Montreal, Montreal, QC, Canada
fYear
2014
fDate
23-25 Sept. 2014
Firstpage
495
Lastpage
499
Abstract
Virtual metrology in quality control deals with drifts in product quality that occur during non-sampling periods. This approach enables a hundred percent control and improves the precision of statistical control, specially while there is no sampling activity in manufacturing process. The main challenge in virtual metrology is inaccurate predictions. As such, the choice of an appropriate algorithm for prediction is crucial. We compare several algorithms that can be used for prediction in virtual metrology. The comparison over different prediction algorithms is made on a simulated data inspired from virtual metrology application.
Keywords
manufacturing processes; measurement; product quality; quality control; classification algorithms; hundred percent control; manufacturing process; nonsampling periods; prediction algorithms; product quality; quality control; sampling activity; statistical control; virtual metrology application; Biological system modeling; Manufacturing; Metrology; Neural networks; Prediction algorithms; Semiconductor device modeling; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Management of Innovation and Technology (ICMIT), 2014 IEEE International Conference on
Conference_Location
Singapore
Type
conf
DOI
10.1109/ICMIT.2014.6942477
Filename
6942477
Link To Document