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
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;
Conference_Titel :
Management of Innovation and Technology (ICMIT), 2014 IEEE International Conference on
Conference_Location :
Singapore
DOI :
10.1109/ICMIT.2014.6942477