A novel statistical method for automatically partitioning tools according to engineers' tolerance control in process improvement

Kevin Kai Wen Tu, Jack Chao Sheng Lee, Henry Horng Shing Lu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In the semiconductor industry, tool comparison is a key task in yield or product quality enhancements. We develop a new method to automatically partition tools. The new method is called tolerance control partitioning (TCP). The advantages of TCP include 1) taking into account of unbalanced tool usage in manufacturing processes; 2) further partitioning these tools into several homogenous groups by related metrology results instead of detecting only the significant difference; and 3) partitioning these tools according to engineers' tolerance controls to avoid too many groups with small differences. TCP also could be applied in all similar cases such as experimental recipe or material comparisons. Therefore, using TCP, engineers could speed up yield or product quality ramping. Two simulation cases illustrate the advantages of TCP method. We also applied TCP to two real cases for yield and Cp/Cpk enhancement in the semiconductor industry. The results confirm the practical feasibility of this method.

Original languageEnglish
Article number5159414
Pages (from-to)373-380
Number of pages8
JournalIEEE Transactions on Semiconductor Manufacturing
Volume22
Issue number3
DOIs
StatePublished - 28 Sep 2009

Keywords

  • APC
  • Bayesian fit
  • C
  • C
  • CART
  • Data mining
  • Process capability
  • Reversible jump Markov chain Monte Carlo
  • Yield enhanceme

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