A hypothesis verification method using regression tree for semiconductor yield analysis

Hidetaka Tsuda*, Hidehiro Shirai, Masahiro Terabe, Kazuo Hashimoto, Ayumi Shinohara

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Several researchers have reported the regression tree analysis for semiconductor yield. However, the scope of these analyses is restricted by the difficulty involved in applying the regression tree analysis to a small number of samples with many attributes. It is often observed that splitting attributes in the route node do not indicate the hypothesized causes of failure. We propose a method for verifying the hypothesized causes of failure, which reduces the number of verification hypotheses. Our method involves selecting sets of analysis data with the same cause of failure, extracting the hypothesis by applying the regression tree analysis separately to each set of analysis data, and merging and sorting attributes according to the t value. The results of an experiment conducted in a real environment show that the proposed method helps in widening the scope of applicability of the regression tree analysis for semiconductor yield.

Original languageEnglish
Pages (from-to)1232-1239
Number of pages8
Journalieej transactions on industry applications
Volume131
Issue number10
DOIs
Publication statusPublished - 2011 Nov 7
Externally publishedYes

Keywords

  • Attribute
  • Failure cause identification
  • Hypothesis verification
  • Regression tree analysis
  • Semiconductor
  • Yield analysis

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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