PittsburghV1, Main, Exploration, bibRecord, 000203

Special session: Hot topics: Statistical test methods

Identifieur interne : 000203 ( Main/Exploration ); précédent : 000202; suivant : 000204

Special session: Hot topics: Statistical test methods

Auteurs : Manuel J. Barragan [France] ; Gildas Leger [Espagne] ; Florence Azaïs [France] ; R. D. Blanton [États-Unis] ; Adit D. Singh [États-Unis] ; Stephen Sunter [Allemagne]

Source :

RBID : Hal:hal-01177043

English descriptors

mix :
- Integrated Circuits.

Abstract

The process of testing Integrated Circuits involves a huge amount of data: electrical circuit measurements, information from wafer process monitors, spatial location of the dies, wafer lot numbers, etc. In addition, the relationships between faults, process variations and circuit performance are likely to be very complex and non-linear. Test (and its extension to diagnosis) should be considered as a challenging highly dimensional multivariate problem.Advanced statistical data processing offers a powerful set of tools, borrowed from the fields of data mining, machine learning or artificial intelligence, to get the most out of this data. Indeed, these mathematical tools have opened a number of novel and interesting research lines within the field of IC testing.In this special session, prominent researchers in this field will share their views on this topic and present some of their last findings. The first talk will discuss the interest of likelihood prevalence in random fault simulation. The second talk will show how statistical data analysis can help diagnosing test efficiency. The third talk will deal with the reliability of Alternate Test of AMS-RF circuits. The fourth and last talk will address the idea of mining the test data for improving design manufacturing and even test itself.

Url:

https://hal.archives-ouvertes.fr/hal-01177043

DOI: 10.1109/VTS.2015.7116265

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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          <date type="start">1939-10-19</date>
          <desc>            <address>              <country key="FR"></country>
            </address>
            <ref type="url">http://www.cnrs.fr/</ref>
          </desc>
        </org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>France</country>
</affiliation>
</author>
<author><name sortKey="Blanton, R D" sort="Blanton, R D" uniqKey="Blanton R" first="R. D." last="Blanton">R. D. Blanton</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-5505" status="INCOMING"><orgName>Carnegie Mellon University, Department of Engineering and Public Policy</orgName>
<orgName type="acronym">CMU, EPP</orgName>
<desc><address><country key="US"></country>
</address>
<ref type="url">http://www.epp.cmu.edu/</ref>
</desc>
<listRelation><relation active="#struct-67135" type="direct"></relation>
</listRelation>
<tutelles><tutelle active="#struct-67135" type="direct"><org type="institution" xml:id="struct-67135" status="VALID">          <orgName>Carnegie Mellon University [Pittsburgh]</orgName>
          <orgName type="acronym">CMU</orgName>
          <desc>            <address>              <addrLine>5000 Forbes Ave,  Pittsburgh, PA 15213</addrLine>
              <country key="US"></country>
            </address>
            <ref type="url">http://www.cmu.edu/</ref>
          </desc>
        </org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>États-Unis</country>
</affiliation>
</author>
<author><name sortKey="Singh, Adit D" sort="Singh, Adit D" uniqKey="Singh A" first="Adit D." last="Singh">Adit D. Singh</name>
<affiliation wicri:level="1"><hal:affiliation type="institution" xml:id="struct-233457" status="VALID"><orgName>Auburn University</orgName>
<orgName type="acronym">AU</orgName>
<date type="start">2016-09-28</date>
<desc><address><addrLine>Auburn UniversityAuburn, Alabama 36849</addrLine>
<country key="US"></country>
</address>
<ref type="url">http://www.auburn.edu/</ref>
</desc>
</hal:affiliation>
<country>États-Unis</country>
</affiliation>
</author>
<author><name sortKey="Sunter, Stephen" sort="Sunter, Stephen" uniqKey="Sunter S" first="Stephen" last="Sunter">Stephen Sunter</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-253810" status="VALID"><orgName>Mentor Graphics</orgName>
<desc><address><addrLine>Tempowerkring 1, Hamburg</addrLine>
<country key="DE"></country>
</address>
<ref type="url">http://www.mentor.com/germany/</ref>
</desc>
<listRelation><relation active="#struct-304825" type="direct"></relation>
</listRelation>
<tutelles><tutelle active="#struct-304825" type="direct"><org type="institution" xml:id="struct-304825" status="INCOMING"><orgName>Mentor Graphics</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>Allemagne</country>
</affiliation>
</author>
</analytic>
<idno type="DOI">10.1109/VTS.2015.7116265</idno>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Integrated Circuits</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">The process of testing Integrated Circuits involves a huge amount of data: electrical circuit measurements, information from wafer process monitors, spatial location of the dies, wafer lot numbers, etc. In addition, the relationships between faults, process variations and circuit performance are likely to be very complex and non-linear. Test (and its extension to diagnosis) should be considered as a challenging highly dimensional multivariate problem.Advanced statistical data processing offers a powerful set of tools, borrowed from the fields of data mining, machine learning or artificial intelligence, to get the most out of this data. Indeed, these mathematical tools have opened a number of novel and interesting research lines within the field of IC testing.In this special session, prominent researchers in this field will share their views on this topic and present some of their last findings. The first talk will discuss the interest of likelihood prevalence in random fault simulation. The second talk will show how statistical data analysis can help diagnosing test efficiency. The third talk will deal with the reliability of Alternate Test of AMS-RF circuits. The fourth and last talk will address the idea of mining the test data for improving design manufacturing and even test itself.</div>
</front>
</TEI>
<affiliations><list><country><li>Allemagne</li>
<li>Espagne</li>
<li>France</li>
<li>États-Unis</li>
</country>
<region><li>Auvergne-Rhône-Alpes</li>
<li>Rhône-Alpes</li>
</region>
<settlement><li>Grenoble</li>
</settlement>
<orgName><li>Université Grenoble-Alpes</li>
<li>Université Joseph Fourier</li>
<li>Université de Grenoble</li>
</orgName>
</list>
<tree><country name="France"><region name="Auvergne-Rhône-Alpes"><name sortKey="Barragan, Manuel J" sort="Barragan, Manuel J" uniqKey="Barragan M" first="Manuel J." last="Barragan">Manuel J. Barragan</name>
</region>
<name sortKey="Azais, Florence" sort="Azais, Florence" uniqKey="Azais F" first="Florence" last="Azaïs">Florence Azaïs</name>
</country>
<country name="Espagne"><noRegion><name sortKey="Leger, Gildas" sort="Leger, Gildas" uniqKey="Leger G" first="Gildas" last="Leger">Gildas Leger</name>
</noRegion>
</country>
<country name="États-Unis"><noRegion><name sortKey="Blanton, R D" sort="Blanton, R D" uniqKey="Blanton R" first="R. D." last="Blanton">R. D. Blanton</name>
</noRegion>
<name sortKey="Singh, Adit D" sort="Singh, Adit D" uniqKey="Singh A" first="Adit D." last="Singh">Adit D. Singh</name>
</country>
<country name="Allemagne"><noRegion><name sortKey="Sunter, Stephen" sort="Sunter, Stephen" uniqKey="Sunter S" first="Stephen" last="Sunter">Stephen Sunter</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>

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Special session: Hot topics: Statistical test methods

Special session: Hot topics: Statistical test methods

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