A new wafer level latent defect screening methodology for highly reliable DRAM using a response surface method

Junghyun Nam, Sunghoon Chun, Gibum Koo, Yanggi Kim, Byungsoo Moon, Jonghyoung Lim, Jaehoon Joo, Sangseok Kang, Hoonjung Kim, Kyeongseon Shin, Kisang Kang, Sungho Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Screening latent defects in a wafer test process is very important task in both reducing memory manufacturing cost and enhancing the reliability of emerging package products such as SIP, MCP, and WSP. In terms of the package assembly cost, these package products are required to adopt the KGD (known good die) quality level. However, the KGD requires a long burn-in time, added testing time, and high cost equipments. To alleviate these problems, this paper presents a statistical wafer burn-in methodology for the latent defect screen in the wafer test process. The newly proposedmethodology consists of a defect-based wafer burn-in (DBWBI) stress method based on DRAM operation characteristics and a statistical stress optimization method using RSM (response surface method) on the DRAM manufacturing test process. Experimental data shows that package test yields in the immature fabrication process improved by up to 6%. In addition, experimental results show that the proposed methodology can guarantee reliability requirements with a shortened package burn-in time. In conclusion, this methodology realizes a simplified manufacturing test process supporting time to market with high reliability.

Original languageEnglish
Title of host publicationProceedings - International Test Conference 2008, ITC 2008
Publication statusPublished - 2008
EventInternational Test Conference 2008, ITC 2008 - Santa Clara, CA, United States
Duration: 2008 Oct 282008 Oct 30

Publication series

NameProceedings - International Test Conference
ISSN (Print)1089-3539


OtherInternational Test Conference 2008, ITC 2008
Country/TerritoryUnited States
CitySanta Clara, CA

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Applied Mathematics


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