Adaptive High Sigma Yield Prediction
Methods and systems are disclosed for determining a yield of a circuit in semiconductor manufacturing. In one embodiment, a computer implemented method includes performing a first pass of Monte Carlo simulations of the circuit to identify a plurality of failed sampling points in a high sigma region...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Ma Yutao McGaughy Bruce W |
| description | Methods and systems are disclosed for determining a yield of a circuit in semiconductor manufacturing. In one embodiment, a computer implemented method includes performing a first pass of Monte Carlo simulations of the circuit to identify a plurality of failed sampling points in a high sigma region of a statistical distribution, partitioning the plurality of failed sampling points into a plurality of clusters based on angular separation of the plurality of failed sampling points, determining a boundary of each cluster in the plurality of clusters, performing sensitivity analysis from the boundary of the each cluster to identify an estimated closest failed sampling point associated with the each cluster, and performing a second pass of Monte Carlo simulations of the circuit to determine the yield of the circuit using the estimated closest failed sampling point associated with the each cluster and the boundary of each cluster in the plurality of clusters. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2017169147A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2017169147A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2017169147A13</originalsourceid><addsrcrecordid>eNrjZFBxTEksKMksS1XwyEzPUAjOTM9NVIjMTM1JUQgoSk3JTC7JzM_jYWBNS8wpTuWF0twMym6uIc4euqkF-fGpxQWJyal5qSXxocFGBobmhmaWhibmjobGxKkCAGkwJzI</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Adaptive High Sigma Yield Prediction</title><source>esp@cenet</source><creator>Ma Yutao ; McGaughy Bruce W</creator><creatorcontrib>Ma Yutao ; McGaughy Bruce W</creatorcontrib><description>Methods and systems are disclosed for determining a yield of a circuit in semiconductor manufacturing. In one embodiment, a computer implemented method includes performing a first pass of Monte Carlo simulations of the circuit to identify a plurality of failed sampling points in a high sigma region of a statistical distribution, partitioning the plurality of failed sampling points into a plurality of clusters based on angular separation of the plurality of failed sampling points, determining a boundary of each cluster in the plurality of clusters, performing sensitivity analysis from the boundary of the each cluster to identify an estimated closest failed sampling point associated with the each cluster, and performing a second pass of Monte Carlo simulations of the circuit to determine the yield of the circuit using the estimated closest failed sampling point associated with the each cluster and the boundary of each cluster in the plurality of clusters.</description><language>eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2017</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20170615&DB=EPODOC&CC=US&NR=2017169147A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,309,782,887,25571,76555</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20170615&DB=EPODOC&CC=US&NR=2017169147A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Ma Yutao</creatorcontrib><creatorcontrib>McGaughy Bruce W</creatorcontrib><title>Adaptive High Sigma Yield Prediction</title><description>Methods and systems are disclosed for determining a yield of a circuit in semiconductor manufacturing. In one embodiment, a computer implemented method includes performing a first pass of Monte Carlo simulations of the circuit to identify a plurality of failed sampling points in a high sigma region of a statistical distribution, partitioning the plurality of failed sampling points into a plurality of clusters based on angular separation of the plurality of failed sampling points, determining a boundary of each cluster in the plurality of clusters, performing sensitivity analysis from the boundary of the each cluster to identify an estimated closest failed sampling point associated with the each cluster, and performing a second pass of Monte Carlo simulations of the circuit to determine the yield of the circuit using the estimated closest failed sampling point associated with the each cluster and the boundary of each cluster in the plurality of clusters.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2017</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZFBxTEksKMksS1XwyEzPUAjOTM9NVIjMTM1JUQgoSk3JTC7JzM_jYWBNS8wpTuWF0twMym6uIc4euqkF-fGpxQWJyal5qSXxocFGBobmhmaWhibmjobGxKkCAGkwJzI</recordid><startdate>20170615</startdate><enddate>20170615</enddate><creator>Ma Yutao</creator><creator>McGaughy Bruce W</creator><scope>EVB</scope></search><sort><creationdate>20170615</creationdate><title>Adaptive High Sigma Yield Prediction</title><author>Ma Yutao ; McGaughy Bruce W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2017169147A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2017</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Ma Yutao</creatorcontrib><creatorcontrib>McGaughy Bruce W</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ma Yutao</au><au>McGaughy Bruce W</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Adaptive High Sigma Yield Prediction</title><date>2017-06-15</date><risdate>2017</risdate><abstract>Methods and systems are disclosed for determining a yield of a circuit in semiconductor manufacturing. In one embodiment, a computer implemented method includes performing a first pass of Monte Carlo simulations of the circuit to identify a plurality of failed sampling points in a high sigma region of a statistical distribution, partitioning the plurality of failed sampling points into a plurality of clusters based on angular separation of the plurality of failed sampling points, determining a boundary of each cluster in the plurality of clusters, performing sensitivity analysis from the boundary of the each cluster to identify an estimated closest failed sampling point associated with the each cluster, and performing a second pass of Monte Carlo simulations of the circuit to determine the yield of the circuit using the estimated closest failed sampling point associated with the each cluster and the boundary of each cluster in the plurality of clusters.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_US2017169147A1 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Adaptive High Sigma Yield Prediction |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-04T12%3A07%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Ma%20Yutao&rft.date=2017-06-15&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2017169147A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |