Investigations on robust design from the perspective of optimization

Sangmun Shin, Madhumohan S. Govindaluri, Byung Rae Cho

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

Abstract

The issue of robust design optimization compromising statistical analyses and optimization techniques for the development of a production process has received much attention from researchers and practitioners for many years. Response surface methodology is accepted as a standard alternative to modeling imperfectly understood process relationships by estimating the response functions for process parameters. In particular, the dual-response approach and the mean squared error model are well-recognized robust design models. In this paper, we provide comprehensive studies associated with statistical analyses and optimization techniques for robust design optimization using four different robust design models, including those two models. A numerical example is conducted, and comparative studies are performed.

Original languageEnglish
Title of host publicationIIE Annual Conference and Exhibition 2004
Pages7-12
Number of pages6
Publication statusPublished - 2004
EventIIE Annual Conference and Exhibition 2004 - Houston, TX, United States
Duration: May 15 2004May 19 2004

Other

OtherIIE Annual Conference and Exhibition 2004
CountryUnited States
CityHouston, TX
Period5/15/045/19/04

Fingerprint

Design optimization

Keywords

  • Optimization
  • Response surface methodology
  • Robust design

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Shin, S., Govindaluri, M. S., & Cho, B. R. (2004). Investigations on robust design from the perspective of optimization. In IIE Annual Conference and Exhibition 2004 (pp. 7-12)

Investigations on robust design from the perspective of optimization. / Shin, Sangmun; Govindaluri, Madhumohan S.; Cho, Byung Rae.

IIE Annual Conference and Exhibition 2004. 2004. p. 7-12.

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

Shin, S, Govindaluri, MS & Cho, BR 2004, Investigations on robust design from the perspective of optimization. in IIE Annual Conference and Exhibition 2004. pp. 7-12, IIE Annual Conference and Exhibition 2004, Houston, TX, United States, 5/15/04.
Shin S, Govindaluri MS, Cho BR. Investigations on robust design from the perspective of optimization. In IIE Annual Conference and Exhibition 2004. 2004. p. 7-12
Shin, Sangmun ; Govindaluri, Madhumohan S. ; Cho, Byung Rae. / Investigations on robust design from the perspective of optimization. IIE Annual Conference and Exhibition 2004. 2004. pp. 7-12
@inproceedings{7a10195184874c739338cc69c7fbf2ce,
title = "Investigations on robust design from the perspective of optimization",
abstract = "The issue of robust design optimization compromising statistical analyses and optimization techniques for the development of a production process has received much attention from researchers and practitioners for many years. Response surface methodology is accepted as a standard alternative to modeling imperfectly understood process relationships by estimating the response functions for process parameters. In particular, the dual-response approach and the mean squared error model are well-recognized robust design models. In this paper, we provide comprehensive studies associated with statistical analyses and optimization techniques for robust design optimization using four different robust design models, including those two models. A numerical example is conducted, and comparative studies are performed.",
keywords = "Optimization, Response surface methodology, Robust design",
author = "Sangmun Shin and Govindaluri, {Madhumohan S.} and Cho, {Byung Rae}",
year = "2004",
language = "English",
pages = "7--12",
booktitle = "IIE Annual Conference and Exhibition 2004",

}

TY - GEN

T1 - Investigations on robust design from the perspective of optimization

AU - Shin, Sangmun

AU - Govindaluri, Madhumohan S.

AU - Cho, Byung Rae

PY - 2004

Y1 - 2004

N2 - The issue of robust design optimization compromising statistical analyses and optimization techniques for the development of a production process has received much attention from researchers and practitioners for many years. Response surface methodology is accepted as a standard alternative to modeling imperfectly understood process relationships by estimating the response functions for process parameters. In particular, the dual-response approach and the mean squared error model are well-recognized robust design models. In this paper, we provide comprehensive studies associated with statistical analyses and optimization techniques for robust design optimization using four different robust design models, including those two models. A numerical example is conducted, and comparative studies are performed.

AB - The issue of robust design optimization compromising statistical analyses and optimization techniques for the development of a production process has received much attention from researchers and practitioners for many years. Response surface methodology is accepted as a standard alternative to modeling imperfectly understood process relationships by estimating the response functions for process parameters. In particular, the dual-response approach and the mean squared error model are well-recognized robust design models. In this paper, we provide comprehensive studies associated with statistical analyses and optimization techniques for robust design optimization using four different robust design models, including those two models. A numerical example is conducted, and comparative studies are performed.

KW - Optimization

KW - Response surface methodology

KW - Robust design

UR - http://www.scopus.com/inward/record.url?scp=30044437977&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=30044437977&partnerID=8YFLogxK

M3 - Conference contribution

SP - 7

EP - 12

BT - IIE Annual Conference and Exhibition 2004

ER -