Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling

C.P.L. Veeger; L.F.P. Etman; J. Herk, van; J.E. Rooda

doi:10.1109/ASMC.2009.5155958

Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling

C.P.L. Veeger, L.F.P. Etman, J. Herk, van, J.E. Rooda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

162 Downloads (Pure)

Abstract

Predicting the mean cycle time as a function of throughput and product mix is helpful in making the production planning for cluster tools. To predict the mean cycle time, detailed simulation models may be used. However, detailed models require much development time, and it may not be possible to estimate all model parameters. Instead of a detailed simulation model, we propose to use a so-calledaggregate model to predict the mean cycle time as a function of throughput and product mix. The aggregate model is a lumped-parameter representation of the queueing system. We estimate the parameters of the aggregate model from arrival and departure data using the Effective Process Time (EPT) concept. The proposedmethod is illustrated for a simulation test case and a Crolles2 cluster tool workstation. The method accurately predicts the mean cycle time in a region around the workstations' operational product mix.

Original language	English
Title of host publication	Proceedings of the 20th Annual IEEE/SEMI Advanced Semiconductor Manufacturing Conference (ASMC 2009)
Place of Publication	Germany, Berlin
Pages	80-85
DOIs	https://doi.org/10.1109/ASMC.2009.5155958
Publication status	Published - 2009
Event	20th Annual IEEE/SEMI Asvanced Semiconductor Manufacturing Conference (ASMC 2009) - Berlin, Germany Duration: 10 May 2009 → 12 May 2009 Conference number: 20

Conference

Conference	20th Annual IEEE/SEMI Asvanced Semiconductor Manufacturing Conference (ASMC 2009)
Abbreviated title	ASMC 2009
Country/Territory	Germany
City	Berlin
Period	10/05/09 → 12/05/09

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10.1109/ASMC.2009.5155958

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Veeger, C. P. L., Etman, L. F. P., Herk, van, J., & Rooda, J. E. (2009). Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling. In Proceedings of the 20th Annual IEEE/SEMI Advanced Semiconductor Manufacturing Conference (ASMC 2009) (pp. 80-85). https://doi.org/10.1109/ASMC.2009.5155958

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title = "Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling",

abstract = "Predicting the mean cycle time as a function of throughput and product mix is helpful in making the production planning for cluster tools. To predict the mean cycle time, detailed simulation models may be used. However, detailed models require much development time, and it may not be possible to estimate all model parameters. Instead of a detailed simulation model, we propose to use a so-calledaggregate model to predict the mean cycle time as a function of throughput and product mix. The aggregate model is a lumped-parameter representation of the queueing system. We estimate the parameters of the aggregate model from arrival and departure data using the Effective Process Time (EPT) concept. The proposedmethod is illustrated for a simulation test case and a Crolles2 cluster tool workstation. The method accurately predicts the mean cycle time in a region around the workstations' operational product mix.",

author = "C.P.L. Veeger and L.F.P. Etman and {Herk, van}, J. and J.E. Rooda",

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Veeger, CPL, Etman, LFP, Herk, van, J & Rooda, JE 2009, Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling. in Proceedings of the 20th Annual IEEE/SEMI Advanced Semiconductor Manufacturing Conference (ASMC 2009). Germany, Berlin, pp. 80-85, 20th Annual IEEE/SEMI Asvanced Semiconductor Manufacturing Conference (ASMC 2009), Berlin, Germany, 10/05/09. https://doi.org/10.1109/ASMC.2009.5155958

Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling. / Veeger, C.P.L.; Etman, L.F.P.; Herk, van, J. et al.
Proceedings of the 20th Annual IEEE/SEMI Advanced Semiconductor Manufacturing Conference (ASMC 2009). Germany, Berlin, 2009. p. 80-85.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Herk, van, J.

AU - Rooda, J.E.

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AB - Predicting the mean cycle time as a function of throughput and product mix is helpful in making the production planning for cluster tools. To predict the mean cycle time, detailed simulation models may be used. However, detailed models require much development time, and it may not be possible to estimate all model parameters. Instead of a detailed simulation model, we propose to use a so-calledaggregate model to predict the mean cycle time as a function of throughput and product mix. The aggregate model is a lumped-parameter representation of the queueing system. We estimate the parameters of the aggregate model from arrival and departure data using the Effective Process Time (EPT) concept. The proposedmethod is illustrated for a simulation test case and a Crolles2 cluster tool workstation. The method accurately predicts the mean cycle time in a region around the workstations' operational product mix.

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ER -

Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling

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