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Paper Abstract and Keywords
Presentation 2014-11-28 15:10
A Method of Burn-in Fail Prediction of LSIs Based on Supervised Learning Using Cluster Analysis
Shogo Tetsukawa, Seiya Miyamoto, Satoshi Ohtake (Oita Univ.), Yoshiyuki Nakamura (Renesas) VLD2014-110 DC2014-64
Abstract (in Japanese) (See Japanese page) 
(in English) Production test of LSIs consists of several test phases such as wafer test phase, package test phase, burn-in test phase, and so on. Since the burn-in test phase spends a lot of time, shortening of or finding replacement for this phase makes the test cost reduced. In this work, a method to learn burn-in fails using production test results of LSIs produced in the past including burn-in test results and to predict burn-in fails of newly produced LSIs using their test results before burn-in test phase is used. The test results of LSIs includes various variabilities such as production induced and measurement induced variabilities. In this paper, we try not to remove the variabilities from the test results but introduce cluster analysis, which is expected to classify dies with similar characteristic including variabilities into the same cluster and to alleviate variabilities in each cluster, into supervised learning
for improved prediction accuracy.
Keyword (in Japanese) (See Japanese page) 
(in English) test cost reduction / fail die prediction / supervised learning / cluster analysis / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 329, DC2014-64, pp. 251-256, Nov. 2014.
Paper # DC2014-64 
Date of Issue 2014-11-19 (VLD, DC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
and
reproduction
技術研究報告に掲載された論文の著作権はIEICEに帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF VLD2014-110 DC2014-64

Conference Information
Committee VLD DC IPSJ-SLDM CPSY RECONF ICD CPM  
Conference Date 2014-11-26 - 2014-11-28 
Place (in Japanese) (See Japanese page) 
Place (in English) B-ConPlaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Design Gaia 2014 -New Field of VLSI Design- 
Paper Information
Registration To DC 
Conference Code 2014-11-VLD-DC-SLDM-CPSY-RECONF-ICD-CPM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Method of Burn-in Fail Prediction of LSIs Based on Supervised Learning Using Cluster Analysis 
Sub Title (in English)  
Keyword(1) test cost reduction  
Keyword(2) fail die prediction  
Keyword(3) supervised learning  
Keyword(4) cluster analysis  
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1st Author's Name Shogo Tetsukawa  
1st Author's Affiliation Oita University (Oita Univ.)
2nd Author's Name Seiya Miyamoto  
2nd Author's Affiliation Oita University (Oita Univ.)
3rd Author's Name Satoshi Ohtake  
3rd Author's Affiliation Oita University (Oita Univ.)
4th Author's Name Yoshiyuki Nakamura  
4th Author's Affiliation Renesas Semiconductor Package & Test Solutions Co.,Ltd. (Renesas)
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Speaker
Date Time 2014-11-28 15:10:00 
Presentation Time 25 
Registration for DC 
Paper # IEICE-VLD2014-110,IEICE-DC2014-64 
Volume (vol) IEICE-114 
Number (no) no.328(VLD), no.329(DC) 
Page pp.251-256 
#Pages IEICE-6 
Date of Issue IEICE-VLD-2014-11-19,IEICE-DC-2014-11-19 


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