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SoC Defect Level Estimation and Reduction by Multi-Model Sampling

Research Project

Project/Area Number 19K11884
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 60040:Computer system-related
Research InstitutionNihon University

Principal Investigator

ARAI Masayuki  日本大学, 生産工学部, 教授 (10336521)

Project Period (FY) 2019-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2021: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywordsマルチモデルサンプリング / 欠陥レベル / ウェハマップ欠陥パターン / クリティカルエリア / ウェハマップ / 欠陥レベル削減 / 欠陥レベル見積り / DPPM / LSI欠陥位置推定 / クリティカルエリアサンプリング / 重み付き故障カバレージ / LSIテストパターン生成 / ブリッジ故障モデル
Outline of Research at the Start

本研究の目的は,超微細プロセスで製造された大規模半導体デバイスに対して,その市場不良率(欠陥レベル)を高精度に見積もる手法,および欠陥レベルを高度に削減可能なテストパターン生成法の開発である.国内半導体産業の動向を鑑み,製造プロセスを持たないファブレス企業での利用を想定したフローの開発を目指す.
まず,個別の故障動作について解析する.次に,チップ全体での欠陥レベル見積もり法について検討する.その後,欠陥レベルを削減するためのテストパターン生成法について検討する.

Outline of Final Research Achievements

In this study, we mainly focused on (A) development and improvement of AI-based defect location and pattern estimation methods, and (B) test pattern generation methods based on the results of defect behavior analysis. For (A), we developed a method to estimate defect locations and patterns with high accuracy based on a small amount of defect information, focusing on both LSI devices and layouts. For (B), we developed a test pattern generation method that takes into account defect behavior under power consumption constraints. The combination of these methods is expected to enable accurate estimation and reduction of defect levels in large-scale semiconductor devices.

Academic Significance and Societal Importance of the Research Achievements

近年,半導体産業の構造が世界的に変化し,日本においては国内での最先端プロセスでの製造(ファブ)が一旦ほぼ断絶した後に回帰しつつある.本研究開発した要素技術の組合せによって,製造されたLSIの信頼性向上,および製造コスト削減が可能となると期待され,学術的意義および産業界に対する貢献は大きいと考えられる.

Report

(6 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (16 results)

All 2023 2022 2021 2020 2019

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (14 results) (of which Int'l Joint Research: 8 results)

  • [Journal Article] Layout Feature Extraction using CNN Classification in Root Cause Analysis of LSI Defects2021

    • Author(s)
      Yoshikazu Nagamura, Koji Arima, Masayuki Arai, Satoshi Fukumoto
    • Journal Title

      IEEE Transactions on Semiconductor Manufacturing

      Volume: Early Access Issue: 2 Pages: 153-160

    • DOI

      10.1109/tsm.2021.3056717

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] CNN-based Layout Segment Classification for Analysis of Layout-induced Failures2020

    • Author(s)
      Yoshikazu Nagamura, Takashi Ide, Masayuki Arai, Satoshi Fukumoto
    • Journal Title

      IEEE Transactions on Semiconductor Manufacturing

      Volume: 33 Issue: 4 Pages: 597-605

    • DOI

      10.1109/tsm.2020.3029049

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Presentation] An Estimation Method of Defect Types Using Artificial Neural Networks and Fault Detection Information2023

    • Author(s)
      Natsuki Ota , Toshinori Hosokawa , Koji Yamazaki , Yukari Yamauchi , Masayuki Arai
    • Organizer
      IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT 2023)
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Toward Improvement and Evaluation of Reconstruction Capability of CapsNet-Based Wafer Map Defect Pattern Classifier2023

    • Author(s)
      Yuki Yamanaka , Masayuki Arai , Yoshikazu Nagamura , Satoshi Fukumoto
    • Organizer
      THE 7TH IEEE INTERNATIONAL TEST CONFERENCE IN ASIA (ITC-ASIA) 2023
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] CapsNetを用いた高解像度ウェハマップの欠陥パターン分類法におけるScratch再構成に関する考察2023

    • Author(s)
      山中祐輝,永村美一,新井雅之,福本聡
    • Organizer
      組込み技術とネットワークに関するワークショップ (ETNET2023)
    • Related Report
      2022 Research-status Report
  • [Presentation] レイアウト起因LSI欠陥検出のためのFSGANを用いたデータ拡張に関する検討2023

    • Author(s)
      杉岡拓海,永村美一,新井雅之,福本聡
    • Organizer
      電子情報通信学会ディペンダブルコンピューティング研究会
    • Related Report
      2022 Research-status Report
  • [Presentation] CapsNetを用いた高解像度ウェハマップの欠陥パターン分類法に関する考察2022

    • Author(s)
      山中祐輝,永村美一,新井雅之,福本聡
    • Organizer
      電子情報通信学会ディペンダブルコンピューティング研究会,コンピュータシステム研究会,情報処理学会システム・アーキテクチャ研究会合同研究会(HotSPA2022)
    • Related Report
      2022 Research-status Report
  • [Presentation] An Estimation Method of Defect Types for Suspected Logical Faulty Lines Using Artificial Neural Networks and Fault Detection Information of Universal Logical Fault Model2021

    • Author(s)
      Natsuki Ohta, Toshinori Hosokawa, Koji Yamazaki, Yukari Yamauchi and Masayuki Arai
    • Organizer
      IEEE Workshop on RTL and High Level Test (WRTLT 2021)
    • Related Report
      2021 Research-status Report
    • Int'l Joint Research
  • [Presentation] Note on CapsNet-Based Wafer Map Defect Pattern Classification2021

    • Author(s)
      Itsuki Fujita, Yoshikazu Nagamura, Masayuki Arai, Satoshi Fukumoto
    • Organizer
      IEEE Asian Test Symposium
    • Related Report
      2021 Research-status Report
  • [Presentation] Evaluation of CNN-Based Defect Location Estimation on LSI Layouts2020

    • Author(s)
      Yoshikazu Nagamura, Masayuki Arai and Satoshi Fukumoto
    • Organizer
      IEEE Workshop on RTL & High Level Testing (WRTLT 2020)
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Presentation] Multiple Target Test Generation Method for Gate-Exhaustive Faults to Reduce the Number of Test Patterns Using Partial MaxSAT2020

    • Author(s)
      Ryuki Asami, Toshinori Hosokawa, Masayoshi Yoshimura, Masayuki Arai
    • Organizer
      The 33rd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT 2020)
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Presentation] パーシャルMAX-SATを用いた抵抗性オープン故障に対するテスト生成法2020

    • Author(s)
      山崎紘史,石山悠太,松田竜馬,細川利典,吉村正義,新井雅之,四柳浩之,橋爪正樹
    • Organizer
      電子情報通信学会ハードウェアセキュリティ研究会
    • Related Report
      2019 Research-status Report
  • [Presentation] A Fine-Grained SDN Rule Table Partitioning and Distribution2019

    • Author(s)
      Yutaro Yoshikawa, Masayuki Arai
    • Organizer
      IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2019)
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] A Don't Care Identification-Filling Co-Optimization Method for Low Capture Power Testing Using Partial MaxSAT2019

    • Author(s)
      Kenichiro Misawa, Toshinori Hosokawa, Hiroshi Yamazaki, Masayoshi Yoshimura and Masayuki Arai
    • Organizer
      IEEE Workshop on RTL & High Level Testing (WRTLT 2019)
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] A Low Capture Power Oriented X-filling Method Using Partial MaxSAT Iteratively2019

    • Author(s)
      T. Hosokawa, K. Misawa, Y. Hirama, H.Yamazaki, M. Yoshimura and M. Arai
    • Organizer
      The 32nd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT 2019)
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] SATを用いたSDNルールテーブル分割法の高速化に関する検討2019

    • Author(s)
      好川雄太郎,新井雅之
    • Organizer
      電子情報通信学会ディペンダブルコンピューティング研究会
    • Related Report
      2019 Research-status Report

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Published: 2019-04-18   Modified: 2025-01-30  

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