March-based RAM diagnosis algorithms for stuck-at and coupling faults

Jin Fu Li, Kuo Liang Cheng, Chih Tsun Huang, Cheng Wen Wu

Research output: Contribution to journalConference article

50 Citations (Scopus)

Abstract

Diagnosis technique plays a key role during the rapid development of the semiconductor memories, for catching the design and manufacturing failures and improving the overall yield and quality. Investigation on efficient diagnosis algorithms is very important due to the expensive and complex fault/failure analysis process. We propose March-based RAM diagnosis algorithms which not only locate faulty cells but also identify their types. The diagnosis complexity is O(17N) and O((17 + 10B)N) for bit-oriented and word-oriented diagnosis algorithms, respectively, where N represents the address number and B is the data width. Using the proposed algorithms, stuck-at faults, state coupling faults, idempotent coupling faults and inversion coupling faults can be distinguished. Furthermore, the coupled and coupling cells can be located in the memory array. Our word-oriented diagnosis algorithm can distinguish all of the inter-word and intra-word coupling faults, and locate the coupling cells of the intra-word inversion and idempotent coupling faults. With additional 2B - 1 operations, the algorithm can further locate the intra-word state coupling faults. With improved diagnostic resolution and test time, the proposed algorithms facilitate the development and manufacturing of semiconductor memories.

Original languageEnglish
Pages (from-to)758-767
Number of pages10
JournalIEEE International Test Conference (TC)
Publication statusPublished - 2001 Dec 1
EventInternational Test Conference 2001 Proceedings - Baltimore, MD, United States
Duration: 2001 Oct 302001 Nov 1

Fingerprint

Random access storage
Fault
Data storage equipment
Idempotent
Semiconductors
Cell
Inversion
Semiconductor materials
Manufacturing
Fault Analysis
Failure Analysis
Failure analysis
Diagnostics

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

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title = "March-based RAM diagnosis algorithms for stuck-at and coupling faults",
abstract = "Diagnosis technique plays a key role during the rapid development of the semiconductor memories, for catching the design and manufacturing failures and improving the overall yield and quality. Investigation on efficient diagnosis algorithms is very important due to the expensive and complex fault/failure analysis process. We propose March-based RAM diagnosis algorithms which not only locate faulty cells but also identify their types. The diagnosis complexity is O(17N) and O((17 + 10B)N) for bit-oriented and word-oriented diagnosis algorithms, respectively, where N represents the address number and B is the data width. Using the proposed algorithms, stuck-at faults, state coupling faults, idempotent coupling faults and inversion coupling faults can be distinguished. Furthermore, the coupled and coupling cells can be located in the memory array. Our word-oriented diagnosis algorithm can distinguish all of the inter-word and intra-word coupling faults, and locate the coupling cells of the intra-word inversion and idempotent coupling faults. With additional 2B - 1 operations, the algorithm can further locate the intra-word state coupling faults. With improved diagnostic resolution and test time, the proposed algorithms facilitate the development and manufacturing of semiconductor memories.",
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March-based RAM diagnosis algorithms for stuck-at and coupling faults. / Li, Jin Fu; Cheng, Kuo Liang; Huang, Chih Tsun; Wu, Cheng Wen.

In: IEEE International Test Conference (TC), 01.12.2001, p. 758-767.

Research output: Contribution to journalConference article

TY - JOUR

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AU - Li, Jin Fu

AU - Cheng, Kuo Liang

AU - Huang, Chih Tsun

AU - Wu, Cheng Wen

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N2 - Diagnosis technique plays a key role during the rapid development of the semiconductor memories, for catching the design and manufacturing failures and improving the overall yield and quality. Investigation on efficient diagnosis algorithms is very important due to the expensive and complex fault/failure analysis process. We propose March-based RAM diagnosis algorithms which not only locate faulty cells but also identify their types. The diagnosis complexity is O(17N) and O((17 + 10B)N) for bit-oriented and word-oriented diagnosis algorithms, respectively, where N represents the address number and B is the data width. Using the proposed algorithms, stuck-at faults, state coupling faults, idempotent coupling faults and inversion coupling faults can be distinguished. Furthermore, the coupled and coupling cells can be located in the memory array. Our word-oriented diagnosis algorithm can distinguish all of the inter-word and intra-word coupling faults, and locate the coupling cells of the intra-word inversion and idempotent coupling faults. With additional 2B - 1 operations, the algorithm can further locate the intra-word state coupling faults. With improved diagnostic resolution and test time, the proposed algorithms facilitate the development and manufacturing of semiconductor memories.

AB - Diagnosis technique plays a key role during the rapid development of the semiconductor memories, for catching the design and manufacturing failures and improving the overall yield and quality. Investigation on efficient diagnosis algorithms is very important due to the expensive and complex fault/failure analysis process. We propose March-based RAM diagnosis algorithms which not only locate faulty cells but also identify their types. The diagnosis complexity is O(17N) and O((17 + 10B)N) for bit-oriented and word-oriented diagnosis algorithms, respectively, where N represents the address number and B is the data width. Using the proposed algorithms, stuck-at faults, state coupling faults, idempotent coupling faults and inversion coupling faults can be distinguished. Furthermore, the coupled and coupling cells can be located in the memory array. Our word-oriented diagnosis algorithm can distinguish all of the inter-word and intra-word coupling faults, and locate the coupling cells of the intra-word inversion and idempotent coupling faults. With additional 2B - 1 operations, the algorithm can further locate the intra-word state coupling faults. With improved diagnostic resolution and test time, the proposed algorithms facilitate the development and manufacturing of semiconductor memories.

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