TY - GEN
T1 - Prediction of product layer cycle time using data mining
AU - Hassoun, Michael
PY - 2013
Y1 - 2013
N2 - Based on a simulated non volatile memory (NVM) fab, we show that forecasting the steady state cycle time of process segments is possible using certain segment characteristics. We also show that the cycle time predictability is highly dependent on the choice of the segmentation, with the more efficient segmentation corresponding to the product layers.
AB - Based on a simulated non volatile memory (NVM) fab, we show that forecasting the steady state cycle time of process segments is possible using certain segment characteristics. We also show that the cycle time predictability is highly dependent on the choice of the segmentation, with the more efficient segmentation corresponding to the product layers.
UR - http://www.scopus.com/inward/record.url?scp=84894202990&partnerID=8YFLogxK
U2 - 10.1109/WSC.2013.6721749
DO - 10.1109/WSC.2013.6721749
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AN - SCOPUS:84894202990
SN - 9781479939503
T3 - Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
SP - 3905
EP - 3911
BT - Proceedings of the 2013 Winter Simulation Conference - Simulation
T2 - 2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
Y2 - 8 December 2013 through 11 December 2013
ER -