Open Access System for Information Sharing

Login Library

 

Article
Cited 6 time in webofscience Cited 7 time in scopus
Metadata Downloads

Optimizing a blend of a mixture slurry in chemical mechanical planarization for advanced semiconductor manufacturing using a posterior preference articulation approach to dual response surface optimization SCIE SCOPUS

Title
Optimizing a blend of a mixture slurry in chemical mechanical planarization for advanced semiconductor manufacturing using a posterior preference articulation approach to dual response surface optimization
Authors
Jihoon SeoDong Hee LeeLee, KKangchun LeeKim, KJ
Date Issued
2016-09
Publisher
Wiley Online Library
Abstract
Semiconductors are fabricated through unit processes including photolithography, etching, diffusion, ion implantation, deposition, and planarization processes. Chemical mechanical planarization, which is essential in advanced semiconductor manufacturing processes, aims to achieve high planarity across the wafer surface. This paper presents a case study in which the optimal blend of mixture slurry was obtained to improve the two response variables (material loss and roughness) at the same time. The mixture slurry consists of several pure slurries; when all of the abrasive particles within the slurry are of the same size, the slurry is referred to as a pure slurry. The optimal blend was obtained by applying a multiresponse surface optimization method. In particular, the recently developed posterior approach to dual response surface optimization was employed, which allows the chemical mechanical planarization process engineer to investigate tradeoffs between the two response variables. The two responses were better with the obtained blend than the existing blend. Copyright (c) 2016 John Wiley & Sons, Ltd.
URI
https://oasis.postech.ac.kr/handle/2014.oak/37111
DOI
10.1002/ASMB.2185
ISSN
1524-1904
Article Type
Article
Citation
Applied Stochastic Model in Business and Industry, vol. 32, no. 5, page. 648 - 659, 2016-09
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

김광재KIM, KWANG JAE
Dept. of Industrial & Management Eng.
Read more

Views & Downloads

Browse