A digital image processing model for characteristics capture and analysis of irregular electronic components
Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as s...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Huang, Chien-Yi [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2019 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer-Verlag London Ltd., part of Springer Nature 2019 |
|---|
| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - Springer London, 1985, 102(2019), 9-12 vom: 09. März, Seite 4309-4318 |
|---|---|
| Übergeordnetes Werk: |
volume:102 ; year:2019 ; number:9-12 ; day:09 ; month:03 ; pages:4309-4318 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00170-019-03451-5 |
|---|
| Katalog-ID: |
OLC2026137560 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC2026137560 | ||
| 003 | DE-627 | ||
| 005 | 20230323142039.0 | ||
| 007 | tu | ||
| 008 | 200820s2019 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s00170-019-03451-5 |2 doi | |
| 035 | |a (DE-627)OLC2026137560 | ||
| 035 | |a (DE-He213)s00170-019-03451-5-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 670 |q VZ |
| 100 | 1 | |a Huang, Chien-Yi |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a A digital image processing model for characteristics capture and analysis of irregular electronic components |
| 264 | 1 | |c 2019 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer-Verlag London Ltd., part of Springer Nature 2019 | ||
| 520 | |a Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. | ||
| 650 | 4 | |a Image processing technique | |
| 650 | 4 | |a BGA components | |
| 650 | 4 | |a Component database | |
| 650 | 4 | |a Electronic component characteristics | |
| 700 | 1 | |a Wu, Jiun-Yi |4 aut | |
| 700 | 1 | |a Huang, Eric |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t The international journal of advanced manufacturing technology |d Springer London, 1985 |g 102(2019), 9-12 vom: 09. März, Seite 4309-4318 |w (DE-627)129185299 |w (DE-600)52651-4 |w (DE-576)014456192 |x 0268-3768 |7 nnns |
| 773 | 1 | 8 | |g volume:102 |g year:2019 |g number:9-12 |g day:09 |g month:03 |g pages:4309-4318 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s00170-019-03451-5 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-TEC | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_2018 | ||
| 912 | |a GBV_ILN_2333 | ||
| 951 | |a AR | ||
| 952 | |d 102 |j 2019 |e 9-12 |b 09 |c 03 |h 4309-4318 | ||
| author_variant |
c y h cyh j y w jyw e h eh |
|---|---|
| matchkey_str |
article:02683768:2019----::dgtlmgpoesnmdlocaatrsisatradnlssfr |
| hierarchy_sort_str |
2019 |
| publishDate |
2019 |
| allfields |
10.1007/s00170-019-03451-5 doi (DE-627)OLC2026137560 (DE-He213)s00170-019-03451-5-p DE-627 ger DE-627 rakwb eng 670 VZ Huang, Chien-Yi verfasserin aut A digital image processing model for characteristics capture and analysis of irregular electronic components 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. Image processing technique BGA components Component database Electronic component characteristics Wu, Jiun-Yi aut Huang, Eric aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 102(2019), 9-12 vom: 09. März, Seite 4309-4318 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 https://doi.org/10.1007/s00170-019-03451-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 102 2019 9-12 09 03 4309-4318 |
| spelling |
10.1007/s00170-019-03451-5 doi (DE-627)OLC2026137560 (DE-He213)s00170-019-03451-5-p DE-627 ger DE-627 rakwb eng 670 VZ Huang, Chien-Yi verfasserin aut A digital image processing model for characteristics capture and analysis of irregular electronic components 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. Image processing technique BGA components Component database Electronic component characteristics Wu, Jiun-Yi aut Huang, Eric aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 102(2019), 9-12 vom: 09. März, Seite 4309-4318 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 https://doi.org/10.1007/s00170-019-03451-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 102 2019 9-12 09 03 4309-4318 |
| allfields_unstemmed |
10.1007/s00170-019-03451-5 doi (DE-627)OLC2026137560 (DE-He213)s00170-019-03451-5-p DE-627 ger DE-627 rakwb eng 670 VZ Huang, Chien-Yi verfasserin aut A digital image processing model for characteristics capture and analysis of irregular electronic components 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. Image processing technique BGA components Component database Electronic component characteristics Wu, Jiun-Yi aut Huang, Eric aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 102(2019), 9-12 vom: 09. März, Seite 4309-4318 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 https://doi.org/10.1007/s00170-019-03451-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 102 2019 9-12 09 03 4309-4318 |
| allfieldsGer |
10.1007/s00170-019-03451-5 doi (DE-627)OLC2026137560 (DE-He213)s00170-019-03451-5-p DE-627 ger DE-627 rakwb eng 670 VZ Huang, Chien-Yi verfasserin aut A digital image processing model for characteristics capture and analysis of irregular electronic components 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. Image processing technique BGA components Component database Electronic component characteristics Wu, Jiun-Yi aut Huang, Eric aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 102(2019), 9-12 vom: 09. März, Seite 4309-4318 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 https://doi.org/10.1007/s00170-019-03451-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 102 2019 9-12 09 03 4309-4318 |
| allfieldsSound |
10.1007/s00170-019-03451-5 doi (DE-627)OLC2026137560 (DE-He213)s00170-019-03451-5-p DE-627 ger DE-627 rakwb eng 670 VZ Huang, Chien-Yi verfasserin aut A digital image processing model for characteristics capture and analysis of irregular electronic components 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. Image processing technique BGA components Component database Electronic component characteristics Wu, Jiun-Yi aut Huang, Eric aut Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 102(2019), 9-12 vom: 09. März, Seite 4309-4318 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 https://doi.org/10.1007/s00170-019-03451-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 102 2019 9-12 09 03 4309-4318 |
| language |
English |
| source |
Enthalten in The international journal of advanced manufacturing technology 102(2019), 9-12 vom: 09. März, Seite 4309-4318 volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 |
| sourceStr |
Enthalten in The international journal of advanced manufacturing technology 102(2019), 9-12 vom: 09. März, Seite 4309-4318 volume:102 year:2019 number:9-12 day:09 month:03 pages:4309-4318 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Image processing technique BGA components Component database Electronic component characteristics |
| dewey-raw |
670 |
| isfreeaccess_bool |
false |
| container_title |
The international journal of advanced manufacturing technology |
| authorswithroles_txt_mv |
Huang, Chien-Yi @@aut@@ Wu, Jiun-Yi @@aut@@ Huang, Eric @@aut@@ |
| publishDateDaySort_date |
2019-03-09T00:00:00Z |
| hierarchy_top_id |
129185299 |
| dewey-sort |
3670 |
| id |
OLC2026137560 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2026137560</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230323142039.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00170-019-03451-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2026137560</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00170-019-03451-5-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Huang, Chien-Yi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A digital image processing model for characteristics capture and analysis of irregular electronic components</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag London Ltd., part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Image processing technique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">BGA components</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Component database</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electronic component characteristics</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Jiun-Yi</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Eric</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">The international journal of advanced manufacturing technology</subfield><subfield code="d">Springer London, 1985</subfield><subfield code="g">102(2019), 9-12 vom: 09. März, Seite 4309-4318</subfield><subfield code="w">(DE-627)129185299</subfield><subfield code="w">(DE-600)52651-4</subfield><subfield code="w">(DE-576)014456192</subfield><subfield code="x">0268-3768</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:102</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:9-12</subfield><subfield code="g">day:09</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:4309-4318</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00170-019-03451-5</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2333</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">102</subfield><subfield code="j">2019</subfield><subfield code="e">9-12</subfield><subfield code="b">09</subfield><subfield code="c">03</subfield><subfield code="h">4309-4318</subfield></datafield></record></collection>
|
| author |
Huang, Chien-Yi |
| spellingShingle |
Huang, Chien-Yi ddc 670 misc Image processing technique misc BGA components misc Component database misc Electronic component characteristics A digital image processing model for characteristics capture and analysis of irregular electronic components |
| authorStr |
Huang, Chien-Yi |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)129185299 |
| format |
Article |
| dewey-ones |
670 - Manufacturing |
| delete_txt_mv |
keep |
| author_role |
aut aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0268-3768 |
| topic_title |
670 VZ A digital image processing model for characteristics capture and analysis of irregular electronic components Image processing technique BGA components Component database Electronic component characteristics |
| topic |
ddc 670 misc Image processing technique misc BGA components misc Component database misc Electronic component characteristics |
| topic_unstemmed |
ddc 670 misc Image processing technique misc BGA components misc Component database misc Electronic component characteristics |
| topic_browse |
ddc 670 misc Image processing technique misc BGA components misc Component database misc Electronic component characteristics |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
The international journal of advanced manufacturing technology |
| hierarchy_parent_id |
129185299 |
| dewey-tens |
670 - Manufacturing |
| hierarchy_top_title |
The international journal of advanced manufacturing technology |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 |
| title |
A digital image processing model for characteristics capture and analysis of irregular electronic components |
| ctrlnum |
(DE-627)OLC2026137560 (DE-He213)s00170-019-03451-5-p |
| title_full |
A digital image processing model for characteristics capture and analysis of irregular electronic components |
| author_sort |
Huang, Chien-Yi |
| journal |
The international journal of advanced manufacturing technology |
| journalStr |
The international journal of advanced manufacturing technology |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2019 |
| contenttype_str_mv |
txt |
| container_start_page |
4309 |
| author_browse |
Huang, Chien-Yi Wu, Jiun-Yi Huang, Eric |
| container_volume |
102 |
| class |
670 VZ |
| format_se |
Aufsätze |
| author-letter |
Huang, Chien-Yi |
| doi_str_mv |
10.1007/s00170-019-03451-5 |
| dewey-full |
670 |
| title_sort |
a digital image processing model for characteristics capture and analysis of irregular electronic components |
| title_auth |
A digital image processing model for characteristics capture and analysis of irregular electronic components |
| abstract |
Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
| abstractGer |
Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
| abstract_unstemmed |
Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 |
| container_issue |
9-12 |
| title_short |
A digital image processing model for characteristics capture and analysis of irregular electronic components |
| url |
https://doi.org/10.1007/s00170-019-03451-5 |
| remote_bool |
false |
| author2 |
Wu, Jiun-Yi Huang, Eric |
| author2Str |
Wu, Jiun-Yi Huang, Eric |
| ppnlink |
129185299 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s00170-019-03451-5 |
| up_date |
2024-07-04T03:12:20.265Z |
| _version_ |
1803616507953938432 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2026137560</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230323142039.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00170-019-03451-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2026137560</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00170-019-03451-5-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Huang, Chien-Yi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A digital image processing model for characteristics capture and analysis of irregular electronic components</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag London Ltd., part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Amid diversification, high performance, high integration, and low-cost development in consumer electronic products, the conventional system on board function integration model is giving way to system on chip (SoC). Layout of solder balls under ball grid array (BGA) is getting irregular as system in package (SiP) is integrating multi-chip module and couple of active and passive components along with more complex circuit design. Due to the shortening life cycles of consumer electronic products and frequent new product launches, the incoming inspection operation of electronic components is getting tedious, let alone the component database updates required by mounter are also getting more frequent and time consuming due to increasingly complex and diversified components and soaring demands in characteristic measurement and identification difficulties. This study is aimed at building automated characteristic capture and analysis image processing model for BGA packages of irregular solder ball layout. It employs edge detection to get component body looks and dimensions by enhanced component edge characteristics. A image pre-processing model is used to identify consistency of individual solder ball characteristics with median filter, highlight image characteristics with binary conversion, remove noise with morphology, and connected component labeling to segment area covered by individual characteristic. In addition, a roundness and aspect ratio of the least rectangle-based solder ball characteristics identification method is proposed to determine number of, diameter of, and coordinates of center of border solder balls. The component characteristics acquired by the model comes in ± 3% difference against the actual one in terms of dimension. The model appears a good reference for system packaging operator in component database creation for the launch of new products in terms of reduced time for manual measurement and error as well as loss in mounter capacity. It also serves for electronic components incoming inspection to reduce inspection operation time and simplify the process.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Image processing technique</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">BGA components</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Component database</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Electronic component characteristics</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Jiun-Yi</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Eric</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">The international journal of advanced manufacturing technology</subfield><subfield code="d">Springer London, 1985</subfield><subfield code="g">102(2019), 9-12 vom: 09. März, Seite 4309-4318</subfield><subfield code="w">(DE-627)129185299</subfield><subfield code="w">(DE-600)52651-4</subfield><subfield code="w">(DE-576)014456192</subfield><subfield code="x">0268-3768</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:102</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:9-12</subfield><subfield code="g">day:09</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:4309-4318</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00170-019-03451-5</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2333</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">102</subfield><subfield code="j">2019</subfield><subfield code="e">9-12</subfield><subfield code="b">09</subfield><subfield code="c">03</subfield><subfield code="h">4309-4318</subfield></datafield></record></collection>
|
| score |
7.400487 |