Closing-Down Optimization for Single-Arm Cluster Tools Subject to Wafer Residency Time Constraints

Yan Qiao, Mengchu Zhou, Naiqi Wu, Zhiwu Li, Qinghua Zhu

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


A kind of facilities for wafer fabrication, cluster tools (CTs) need to close down to an idle state from time to time because of periodical maintenance and switches from one type of lots to another, which is called a normal close-down process (NCDP). It is crucial to optimize such a transient process since it tends to occur more and more frequently due to customization. Also, process modules (PMs) in CTs are known to be failure-prone. Once a PM failure occurs, a tool needs to close down to an idle state as well, which is different from NCDP and is called a failure close-down process (FCDP). With wafer residency time constraints (WRTCs) being imposed, close-down process optimization for such a tool is challenging, since one needs to not only finish this process as soon as possible but also meet WRTCs during this transient process. In order to tackle this problem, this article first introduces steady state scheduling problems. Then, with a presented backward robot task sequence, a linear programming model is first proposed to optimize NCDP. To deal with the PM failures, efficient PM failure response policies are formulated for the cases in which a PM fails. Then, four linear programs are proposed to optimize an FCDP. Finally, industrial case studies are given to show the usefulness of the proposed approaches.

Original languageEnglish (US)
Pages (from-to)6792-6807
Number of pages16
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Issue number11
StatePublished - Nov 1 2021

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Cluster tools (CTs)
  • failure response
  • scheduling
  • semiconductor manufacturing


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