TY - JOUR
T1 - Analysis of wafer fabrication facilities using four variations of the open queueing network decomposition model
AU - MILTENBURG, John
AU - CHENG, Chun Hung
AU - YAN, Houmin
N1 - The publication is also published in IIE Transactions (Taylor & Francis)
PY - 2002/3
Y1 - 2002/3
N2 - We analyze three wafer fabrication facilities with four open queueing network decomposition models - Whitt (1983, 1985), and Bitran and Tirupati (1988), Suri et al. (1993). In the first facility, which is located in North America, the values of cycle time and WIP inventory predicted by each model are about 10% higher than the actual values observed in the facility. The estimates are on the high side because managers and operators in the facility take special action to expedite production whenever queues become too large or small. These special actions cannot be incorporated into the open queueing network models. In the second facility, which is taken from the literature, the values of cycle time and WIP predicted by each model are about 5% higher than the values reported in the literature. An investigation at a third facility located in South-east Asia identified a common manufacturing practice that caused a model assumption to be violated. New insights into the models and directions for future research are identified. We find that two of the four open queueing network models are easy to apply and give good results for facilities like the ones studied in this paper. The other two models are complex and are likely to be better-suited for more complex facilities.
AB - We analyze three wafer fabrication facilities with four open queueing network decomposition models - Whitt (1983, 1985), and Bitran and Tirupati (1988), Suri et al. (1993). In the first facility, which is located in North America, the values of cycle time and WIP inventory predicted by each model are about 10% higher than the actual values observed in the facility. The estimates are on the high side because managers and operators in the facility take special action to expedite production whenever queues become too large or small. These special actions cannot be incorporated into the open queueing network models. In the second facility, which is taken from the literature, the values of cycle time and WIP predicted by each model are about 5% higher than the values reported in the literature. An investigation at a third facility located in South-east Asia identified a common manufacturing practice that caused a model assumption to be violated. New insights into the models and directions for future research are identified. We find that two of the four open queueing network models are easy to apply and give good results for facilities like the ones studied in this paper. The other two models are complex and are likely to be better-suited for more complex facilities.
UR - https://www.scopus.com/pages/publications/0036498120
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0036498120&origin=recordpage
U2 - 10.1023/A:1012481300018
DO - 10.1023/A:1012481300018
M3 - RGC 21 - Publication in refereed journal
SN - 0740-817X
VL - 34
SP - 263
EP - 272
JO - IIE Transactions (Institute of Industrial Engineers)
JF - IIE Transactions (Institute of Industrial Engineers)
IS - 3
ER -