Paper Abstract and Keywords |
Presentation |
2016-03-25 15:45
A consideration on variation correction for fail prediction in LSI test Ryo Ogawa (NAIST), Yoshiyuki Nakamura (Renesas Semiconductor Package & Test Solutions), Michiko Inoue (NAIST) CPSY2015-158 DC2015-112 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, a test cost reduction using data mining has been attracted. It is expected to reduce the cost by predicting failing LSIs in later test processes using result of earlier test processes. However measured values in test processes have variation caused by the manufacturing and measurements themselves. Therefore, it is difficult to predict tests results without correction. In this paper, we propose variation correction method that corrects variations among package-lots, testers, and tester-sites respectively. We also propose a method to evaluate the effectiveness of correction and show that the proposed correction method is effective. Finally, we will consider how the proposed correction method is effective to fail prediction during LSI testing. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
data mining / burn-in test / LSI test / variation correction / outlier analysis / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 519, DC2015-112, pp. 271-276, March 2016. |
Paper # |
DC2015-112 |
Date of Issue |
2016-03-17 (CPSY, DC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Notes on Review |
This article is a technical report without peer review, and its polished version will be published elsewhere. |
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CPSY2015-158 DC2015-112 |
Conference Information |
Committee |
CPSY DC IPSJ-SLDM IPSJ-EMB IPSJ-ARC |
Conference Date |
2016-03-24 - 2016-03-25 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Fukue Bunka Hall/Rodou Fukushi Center |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
ETNET2016 |
Paper Information |
Registration To |
DC |
Conference Code |
2016-03-CPSY-DC-SLDM-EMB-ARC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A consideration on variation correction for fail prediction in LSI test |
Sub Title (in English) |
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Keyword(1) |
data mining |
Keyword(2) |
burn-in test |
Keyword(3) |
LSI test |
Keyword(4) |
variation correction |
Keyword(5) |
outlier analysis |
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1st Author's Name |
Ryo Ogawa |
1st Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
2nd Author's Name |
Yoshiyuki Nakamura |
2nd Author's Affiliation |
Renesas Semiconductor Package & Test Solutions (Renesas Semiconductor Package & Test Solutions) |
3rd Author's Name |
Michiko Inoue |
3rd Author's Affiliation |
Nara Institute of Science and Technology (NAIST) |
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Speaker |
Author-1 |
Date Time |
2016-03-25 15:45:00 |
Presentation Time |
25 minutes |
Registration for |
DC |
Paper # |
CPSY2015-158, DC2015-112 |
Volume (vol) |
vol.115 |
Number (no) |
no.518(CPSY), no.519(DC) |
Page |
pp.271-276 |
#Pages |
6 |
Date of Issue |
2016-03-17 (CPSY, DC) |
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