Estimating variance of output from cyclic exponential queueing systems
Queueing Systems: Theory and Applications
Simulation in automated material handling systems design for semiconductor manufacturing
WSC '94 Proceedings of the 26th conference on Winter simulation
Effective simulation model reuse: a case study for AMHS modeling
Proceedings of the 30th conference on Winter simulation
Increasing first pass accuracy of AMHS simulation output using legacy data
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Estimating expected completion times with probabilistic job routing
Proceedings of the 38th conference on Winter simulation
An analytical model of vehicle-based automated material handling systems in semiconductor fabs
Proceedings of the 38th conference on Winter simulation
Survey of research in modeling conveyor-based automated material handling systems in wafer fabs
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Information models for queueing system simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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Queueing networks are sometimes used to model material handling in flexible manufacturing systems. We explore the use of a closed queueing network model to approximate an intrabay automated material handling system (AMHS) in semiconductor manufacturing. Rather than solving the model analytically, we propose simulating it. Current industry models are very complex and require long development and run times. The simulated approximation can be used as an easy and fast alternative. To compare the approximation with the detailed models in use, we employ an information taxonomy to classify AMHS models based on the amount and types of information needed to model the system, and to obtain desired output. This classification aids modelers in determining the level of detail to incorporate in a model based on the objectives of the simulation study.