TY - GEN
T1 - Analysis of Artificial Neural Network Based Algorithms for Real Time Dispatching
AU - Chakravorty, Shiladitya
AU - Nagarur, Nagendra N.
N1 - Publisher Copyright: © 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Queue time restricted zones present some unique challenges for dispatching and scheduling systems in a semiconductor manufacturing facility. In this study we present a real time algorithm for wafer dispatching in queue time zones based on cycle time predictions. Proposed prediction methodologies are based on backpropagation trained artificial neural network and radial basis function based neural network. Results obtained from the artificial neural network models are compared to each other and with a multivariate linear regression model for cycle time prediction.
AB - Queue time restricted zones present some unique challenges for dispatching and scheduling systems in a semiconductor manufacturing facility. In this study we present a real time algorithm for wafer dispatching in queue time zones based on cycle time predictions. Proposed prediction methodologies are based on backpropagation trained artificial neural network and radial basis function based neural network. Results obtained from the artificial neural network models are compared to each other and with a multivariate linear regression model for cycle time prediction.
KW - Artificial Neural Networks
KW - Backpropagation
KW - Factory Automation
KW - Industrial Engineering
KW - Production Scheduling and Dispatching
KW - Radial Basis Function Network
UR - https://www.scopus.com/pages/publications/85132798472
U2 - 10.1109/ASMC54647.2022.9792495
DO - 10.1109/ASMC54647.2022.9792495
M3 - Conference contribution
T3 - ASMC (Advanced Semiconductor Manufacturing Conference) Proceedings
BT - 2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference, ASMC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference, ASMC 2022
Y2 - 2 May 2022 through 5 May 2022
ER -