Yield Estimation of a Memristive Sensor Array

Vishal Gupta; Saurabh Khandelwal; Giulio Panunzi; Eugenio Martinelli; Said Hamdioui; Abusaleh Jabir; Marco Ottavi

doi:10.1109/IOLTS50870.2020.9159727

Yield Estimation of a Memristive Sensor Array

Vishal Gupta, Saurabh Khandelwal, Giulio Panunzi, Eugenio Martinelli, Said Hamdioui, Abusaleh Jabir, Marco Ottavi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

Abstract

This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations.

Original language	English
Title of host publication	Proceedings - 2020 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020
Publisher	IEEE
ISBN (Electronic)	9781728181875
DOIs	https://doi.org/10.1109/IOLTS50870.2020.9159727
Publication status	Published - Jul 2020
Externally published	Yes
Event	26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020 - Virtual, Online, Italy Duration: 13 Jul 2020 → 16 Jul 2020 Conference number: 26 https://www.iolts2020virtual.cloud/welcome/

Conference

Conference	26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020
Abbreviated title	IOLTS 2020
Country/Territory	Italy
City	Virtual, Online
Period	13/07/20 → 16/07/20
Internet address	https://www.iolts2020virtual.cloud/welcome/

Keywords

Gas Sensor
Markov Modeling
Memristor
Redundancy
Yield

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10.1109/IOLTS50870.2020.9159727

Cite this

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title = "Yield Estimation of a Memristive Sensor Array",

abstract = "This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations. ",

keywords = "Gas Sensor, Markov Modeling, Memristor, Redundancy, Yield",

author = "Vishal Gupta and Saurabh Khandelwal and Giulio Panunzi and Eugenio Martinelli and Said Hamdioui and Abusaleh Jabir and Marco Ottavi",

note = "Funding Information: The work was funded by the Leverhulme Trust Research Project Grant, under Grant No.RPG-2017-344. Publisher Copyright: {\textcopyright} 2020 IEEE.; 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020, IOLTS 2020 ; Conference date: 13-07-2020 Through 16-07-2020",

year = "2020",

month = jul,

doi = "10.1109/IOLTS50870.2020.9159727",

language = "English",

booktitle = "Proceedings - 2020 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020",

publisher = "IEEE",

address = "United States",

url = "https://www.iolts2020virtual.cloud/welcome/",

}

Gupta, V, Khandelwal, S, Panunzi, G, Martinelli, E, Hamdioui, S, Jabir, A & Ottavi, M 2020, Yield Estimation of a Memristive Sensor Array. in Proceedings - 2020 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020., 9159727, IEEE, 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020, Virtual, Online, Italy, 13/07/20. https://doi.org/10.1109/IOLTS50870.2020.9159727

TY - GEN

T1 - Yield Estimation of a Memristive Sensor Array

AU - Gupta, Vishal

AU - Khandelwal, Saurabh

AU - Panunzi, Giulio

AU - Martinelli, Eugenio

AU - Hamdioui, Said

AU - Jabir, Abusaleh

AU - Ottavi, Marco

N1 - Conference code: 26

PY - 2020/7

Y1 - 2020/7

N2 - This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations.

AB - This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations.

KW - Gas Sensor

KW - Markov Modeling

KW - Memristor

KW - Redundancy

KW - Yield

UR - http://www.scopus.com/inward/record.url?scp=85091592618&partnerID=8YFLogxK

U2 - 10.1109/IOLTS50870.2020.9159727

DO - 10.1109/IOLTS50870.2020.9159727

M3 - Conference contribution

AN - SCOPUS:85091592618

BT - Proceedings - 2020 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020

PB - IEEE

T2 - 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020

Y2 - 13 July 2020 through 16 July 2020

ER -

Yield Estimation of a Memristive Sensor Array

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Conference

Keywords

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