TY - GEN
T1 - A consolidated approach to minimize semiconductor production loss due to unscheduled ATE downtime
AU - Jin, Tongdan
AU - Belkhouche, Fethi
AU - Sung, Chen Han
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - A production-loss based maintenance plan is proposed to minimize the cost due to unscheduled ATE (Automatic Test Equipment) downtime in the back-end process of semiconductor manufacturing. This paper suggests two methods, active redundancy and cold standby redundancy, to expedite the ATE system repair time for returning the system back to production. This strategy is different from other reliability improvement methods such as corrective actions and preventive maintenance. By reducing the repair time, the system upper time actually increases and hence the production loss is minimized. The optimization is formulated to minimize the production loss considering the system depreciations, lost sales and idle labor when they are subject to maintenance budget and volume constraint. To solve this optimization problem, Genetic Algorithm is used to find the near-optimal solution. The illustrative example demonstrates that using redundant modules is a very effective way to minimize the semiconductor production loss due to unscheduled system downtime.
AB - A production-loss based maintenance plan is proposed to minimize the cost due to unscheduled ATE (Automatic Test Equipment) downtime in the back-end process of semiconductor manufacturing. This paper suggests two methods, active redundancy and cold standby redundancy, to expedite the ATE system repair time for returning the system back to production. This strategy is different from other reliability improvement methods such as corrective actions and preventive maintenance. By reducing the repair time, the system upper time actually increases and hence the production loss is minimized. The optimization is formulated to minimize the production loss considering the system depreciations, lost sales and idle labor when they are subject to maintenance budget and volume constraint. To solve this optimization problem, Genetic Algorithm is used to find the near-optimal solution. The illustrative example demonstrates that using redundant modules is a very effective way to minimize the semiconductor production loss due to unscheduled system downtime.
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U2 - 10.1109/COASE.2007.4341712
DO - 10.1109/COASE.2007.4341712
M3 - Conference contribution
AN - SCOPUS:44449162750
SN - 1424411548
SN - 9781424411542
T3 - Proceedings of the 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007
SP - 188
EP - 193
BT - Proceedings of the 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007
T2 - 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007
Y2 - 22 September 2007 through 25 September 2007
ER -