Predicting Cycle Time Distributions with Aggregate Modelling of Work Areas in a Real-World Wafer Fab

Patrick C. Deenen, Jelle Adan, John W. Fowler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In a semiconductor wafer fabrication facility (wafer fab) it is important to accurately predict wafer outs, i.e. the remaining cycle time of the wafers in process. A wafer fab consists of multiple work areas, each containing a specific process technology, for example, photolithography, metal deposition or etching. Therefore, to accurately predict the wafer outs, an accurate prediction of the cycle time distribution at each work area is essential. This paper proposes an aggregate model to simulate each of these work areas. The aggregate model is a single server with an aggregate process time distribution and an overtaking distribution. Both distributions are WIP-dependent, but an additional layer-type dependency is introduced for the overtaking distribution. Application on a real-world wafer fabrication facility of a semiconductor manufacturer is presented for the work areas of photolithography, oxidation and dry etch. These experiments show that the aggregate model can, under certain circumstances, accurately predict the cycle time distributions in work areas by layer-type.

Original languageEnglish (US)
Title of host publication2021 Winter Simulation Conference, WSC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433112
DOIs
StatePublished - 2021
Externally publishedYes
Event2021 Winter Simulation Conference, WSC 2021 - Phoenix, United States
Duration: Dec 12 2021Dec 15 2021

Publication series

NameProceedings - Winter Simulation Conference
Volume2021-December
ISSN (Print)0891-7736

Conference

Conference2021 Winter Simulation Conference, WSC 2021
Country/TerritoryUnited States
CityPhoenix
Period12/12/2112/15/21

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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