Assessment of potential gains in productivity due to proactive reticle management using discrete event simulation

Sungmin Park, John Fowler, Matt Carlyle, Matt Hickie

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

14 Scopus citations

Abstract

Photolithography is often the constraining equipment in semiconductor wafer fabrication plants due to the number of times the product must process through it. Modern day photolithography is performed on a cluster tool that is a combination of a stepper and track. It is obvious that the combined availability of the cluster tool is critical to throughput, but what is not so obvious is the throughput restriction from a secondary constraint known as a reticle. Every layer of a product needs a unique reticle for processing. Setup issues arising from the requirement of reticles affects productivity of photolithography and the entire wafer fabrication line if photolithography is the bottleneck. Efficient management of reticles (with regard to setup and storage on a stepper) based on current system status provides a strategic and tactical advantage. In this paper, a SLAM discrete event simulation model is to mimic the setup and storage of reticles. This enables the collection of information that can used to identify potential gains in tactical reticle management. The simulation model will be explained in detail along with output results for the tactical issues. The relationship between the simulation and the network flow model for proactive reticle management will also be discussed.

Original languageEnglish (US)
Title of host publicationWinter Simulation Conference Proceedings
PublisherIEEE
Pages856-864
Number of pages9
Volume1
StatePublished - 1999
Event1999 Winter Simulation Conference Proceedings (WSC) - Phoenix, AZ, USA
Duration: Dec 5 1999Dec 8 1999

Other

Other1999 Winter Simulation Conference Proceedings (WSC)
CityPhoenix, AZ, USA
Period12/5/9912/8/99

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Software
  • Safety, Risk, Reliability and Quality
  • Applied Mathematics
  • Modeling and Simulation

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