Modeling, analysis and control of dual-arm cluster tools with residency time constraint and activity time variation based on Petri nets

Nai Qi Wu, Mengchu Zhou

Research output: Contribution to journalArticlepeer-review

166 Scopus citations

Abstract

Because of residency time constraints and activity time variation of cluster tools, it is very difficult to operate such integrated semiconductor manufacturing equipment. This paper addresses their real-time operational issues. To characterize their schedulability and achieve the minimum cycle time at their steady-state operation, Petri net (PN) models are developed to describe them, which are very compact, and independent of wafer flow pattern. It is due to the proposed models that scheduling cluster tools is converted into determining robot wait times. A two-level operational architecture is proposed to include an offline periodic schedule and real-time controller. The former determines when a wafer should be placed into a process module for processing, while the latter regulates robot wait times online in order to reduce the effect of activity time variation on wafer sojourn times in process modules. Therefore, the system can adapt to activity time variation. A cluster tool derived as a not-always-schedulable system by the existing methods is shown to be always-schedulable by using the proposed novel method.

Original languageEnglish (US)
Article number6138879
Pages (from-to)446-454
Number of pages9
JournalIEEE Transactions on Automation Science and Engineering
Volume9
Issue number2
DOIs
StatePublished - Apr 2012

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Automated manufacturing system
  • Petri net (PN)
  • cluster tools
  • discrete event system
  • optimization
  • scheduling
  • semiconductor fabrication

Fingerprint Dive into the research topics of 'Modeling, analysis and control of dual-arm cluster tools with residency time constraint and activity time variation based on Petri nets'. Together they form a unique fingerprint.

Cite this