Nonlinear diffusion process modeling using response surface methodology and variable transformation

Young Don Ko, Yuhee Kim, Dongkwon Park, Ilgu Yun

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The nonlinear process modeling is investigated using statistical design method and response surface methodology. Three input factors are examined with respect to the response factor. In order to minimize the joint confidence region of fabrication process with varying conditions, D-optimal experimental design technique is performed and diffusion rate is characterized by response model. Then, the statistical results are used to verify the fitness of the nonlinear process model. Based on the results, this modeling methodology can be optimized process condition for semiconductor manufacturing.

Original languageEnglish
Pages (from-to)121-125
Number of pages5
JournalRobotics and Computer-Integrated Manufacturing
Volume20
Issue number2
DOIs
Publication statusPublished - 2004 Apr 1

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Variable Transformation
Response Surface Methodology
Nonlinear Process
Nonlinear Diffusion
Process Modeling
Diffusion Process
Optimal Experimental Design
D-optimal
Semiconductor Manufacturing
Nonlinear Modeling
Confidence Region
Design of experiments
Statistical method
Process Model
Fitness
Design Method
Nonlinear Model
Fabrication
Semiconductor materials
Verify

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

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Nonlinear diffusion process modeling using response surface methodology and variable transformation. / Ko, Young Don; Kim, Yuhee; Park, Dongkwon; Yun, Ilgu.

In: Robotics and Computer-Integrated Manufacturing, Vol. 20, No. 2, 01.04.2004, p. 121-125.

Research output: Contribution to journalArticle

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