Kernel-density-based particle defect management for semiconductor manufacturing facilities

Seung Hwan Park, Sehoon Kim, Jun-Geol Baek

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In a semiconductor manufacturing process, defect cause analysis is a challenging task because the process includes consecutive fabrication phases involving numerous facilities. Recently, in accordance with the shrinking chip pitches, fabrication (FAB) processes require advanced facilities and designs for manufacturing microcircuits. However, the sizes of the particle defects remain constant, in spite of the increasing modernization of the facilities. Consequently, this increases the particle defect ratio. Therefore, this study proposes a particle defect management method for the reduction of the defect ratio. The proposed method provides a kernel-density-based particle map that can overcome the limitations of the conventional method. The method consists of two phases. The first phase is the acquisition of cumulative coordinates of the defect locations on the wafer using the FAB database. Subsequently, this cumulative data is used to generate a particle defect map based on the estimation of kernel density; this map establishes the advanced monitoring statistics. In order to validate this method, we conduct an experiment for comparison with the previous industrial method.

Original languageEnglish
Article number224
JournalApplied Sciences (Switzerland)
Volume8
Issue number2
DOIs
Publication statusPublished - 2018 Feb 1

Fingerprint

manufacturing
Semiconductor materials
Defects
defects
Fabrication
fabrication
management methods
Modernization
microelectronics
acquisition
chips
Statistics
statistics
wafers
Monitoring
causes
Experiments

Keywords

  • Kernel density estimation
  • Particle defect management
  • Particle map
  • Semiconductor manufacturing process

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

Cite this

Kernel-density-based particle defect management for semiconductor manufacturing facilities. / Park, Seung Hwan; Kim, Sehoon; Baek, Jun-Geol.

In: Applied Sciences (Switzerland), Vol. 8, No. 2, 224, 01.02.2018.

Research output: Contribution to journalArticle

@article{28bea40e7c8f4afabe5ef2aa8caa8ef0,
title = "Kernel-density-based particle defect management for semiconductor manufacturing facilities",
abstract = "In a semiconductor manufacturing process, defect cause analysis is a challenging task because the process includes consecutive fabrication phases involving numerous facilities. Recently, in accordance with the shrinking chip pitches, fabrication (FAB) processes require advanced facilities and designs for manufacturing microcircuits. However, the sizes of the particle defects remain constant, in spite of the increasing modernization of the facilities. Consequently, this increases the particle defect ratio. Therefore, this study proposes a particle defect management method for the reduction of the defect ratio. The proposed method provides a kernel-density-based particle map that can overcome the limitations of the conventional method. The method consists of two phases. The first phase is the acquisition of cumulative coordinates of the defect locations on the wafer using the FAB database. Subsequently, this cumulative data is used to generate a particle defect map based on the estimation of kernel density; this map establishes the advanced monitoring statistics. In order to validate this method, we conduct an experiment for comparison with the previous industrial method.",
keywords = "Kernel density estimation, Particle defect management, Particle map, Semiconductor manufacturing process",
author = "Park, {Seung Hwan} and Sehoon Kim and Jun-Geol Baek",
year = "2018",
month = "2",
day = "1",
doi = "10.3390/app8020224",
language = "English",
volume = "8",
journal = "Applied Sciences (Switzerland)",
issn = "2076-3417",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "2",

}

TY - JOUR

T1 - Kernel-density-based particle defect management for semiconductor manufacturing facilities

AU - Park, Seung Hwan

AU - Kim, Sehoon

AU - Baek, Jun-Geol

PY - 2018/2/1

Y1 - 2018/2/1

N2 - In a semiconductor manufacturing process, defect cause analysis is a challenging task because the process includes consecutive fabrication phases involving numerous facilities. Recently, in accordance with the shrinking chip pitches, fabrication (FAB) processes require advanced facilities and designs for manufacturing microcircuits. However, the sizes of the particle defects remain constant, in spite of the increasing modernization of the facilities. Consequently, this increases the particle defect ratio. Therefore, this study proposes a particle defect management method for the reduction of the defect ratio. The proposed method provides a kernel-density-based particle map that can overcome the limitations of the conventional method. The method consists of two phases. The first phase is the acquisition of cumulative coordinates of the defect locations on the wafer using the FAB database. Subsequently, this cumulative data is used to generate a particle defect map based on the estimation of kernel density; this map establishes the advanced monitoring statistics. In order to validate this method, we conduct an experiment for comparison with the previous industrial method.

AB - In a semiconductor manufacturing process, defect cause analysis is a challenging task because the process includes consecutive fabrication phases involving numerous facilities. Recently, in accordance with the shrinking chip pitches, fabrication (FAB) processes require advanced facilities and designs for manufacturing microcircuits. However, the sizes of the particle defects remain constant, in spite of the increasing modernization of the facilities. Consequently, this increases the particle defect ratio. Therefore, this study proposes a particle defect management method for the reduction of the defect ratio. The proposed method provides a kernel-density-based particle map that can overcome the limitations of the conventional method. The method consists of two phases. The first phase is the acquisition of cumulative coordinates of the defect locations on the wafer using the FAB database. Subsequently, this cumulative data is used to generate a particle defect map based on the estimation of kernel density; this map establishes the advanced monitoring statistics. In order to validate this method, we conduct an experiment for comparison with the previous industrial method.

KW - Kernel density estimation

KW - Particle defect management

KW - Particle map

KW - Semiconductor manufacturing process

UR - http://www.scopus.com/inward/record.url?scp=85041589375&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041589375&partnerID=8YFLogxK

U2 - 10.3390/app8020224

DO - 10.3390/app8020224

M3 - Article

AN - SCOPUS:85041589375

VL - 8

JO - Applied Sciences (Switzerland)

JF - Applied Sciences (Switzerland)

SN - 2076-3417

IS - 2

M1 - 224

ER -