Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life
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2014
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my.unimap-338532014-04-19T16:22:25Z Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life Lee, Kor Oon Ong, Kang E. Seetharamu, Kankanhally N. Ishak, Abdul Azid, Dr. Ghulam, Abdul Quadir, Prof. Dr. Goh, Teck Joo ishak@eng.usm.my gaquadir@unimap.edu.my Joining materials Reliability management Solders Link to publisher's homepage at http://www.emeraldinsight.com/ Purpose: Aims to present a finite element analysis based methodology for estimating the characteristic fatigue life of a solder joint interconnect under accelerated temperature cycling to predict the reliability performance of a flip chip package. Design/methodology/approach: The method uses the ANSYSTM finite element analysis tool along with Anand's viscoplastic constitutive law. Darveaux's crack growth rate model was applied to calculate solder joint characteristic life using simulated viscoplastic strain energy density results at the package substrate and printed circuit board solder joints. Two package configurations are evaluated with the above methodology, with the first being a simplified flip chip model and the second being a detailed flip chip model. Each of these configurations is subjected to two accelerated temperature cycling tests. Findings: Generally, the results indicate that the solder joint at the corner end of the package tends to fail first. The characteristic lives of solder joint at the package ball/board interface are 24-46 percent higher than the characteristic lives of solder joint at the package ball/substrate interface. This means that the interface between the solder ball and substrate will fail first before the interface between the solder ball and the board. Originality/value: Demonstrates that genetic algorithms can be used as tools to predict possible package dimensional values for given constraints on solder joint life. 2014-04-19T16:22:25Z 2014-04-19T16:22:25Z 2006 Article Microelectronics International, vol. 23(2), 2006, pages 37-44 1356-5362 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33853 http://www.emeraldinsight.com/journals.htm?articleid=1550669 http://dx.doi.org/10.1108/13565360610659707 en Emerald Group Publishing |
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Joining materials Reliability management Solders |
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Joining materials Reliability management Solders Lee, Kor Oon Ong, Kang E. Seetharamu, Kankanhally N. Ishak, Abdul Azid, Dr. Ghulam, Abdul Quadir, Prof. Dr. Goh, Teck Joo Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
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Link to publisher's homepage at http://www.emeraldinsight.com/ |
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ishak@eng.usm.my |
author_facet |
ishak@eng.usm.my Lee, Kor Oon Ong, Kang E. Seetharamu, Kankanhally N. Ishak, Abdul Azid, Dr. Ghulam, Abdul Quadir, Prof. Dr. Goh, Teck Joo |
format |
Article |
author |
Lee, Kor Oon Ong, Kang E. Seetharamu, Kankanhally N. Ishak, Abdul Azid, Dr. Ghulam, Abdul Quadir, Prof. Dr. Goh, Teck Joo |
author_sort |
Lee, Kor Oon |
title |
Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
title_short |
Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
title_full |
Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
title_fullStr |
Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
title_full_unstemmed |
Application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
title_sort |
application of artificial intelligence for the determination of package parameters for a desired solder joint fatigue life |
publisher |
Emerald Group Publishing |
publishDate |
2014 |
url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/33853 |
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1643797317811175424 |
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13.222552 |