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Using design-of-experiments techniques for an efficient finite element study of the influence of changed parameters in design

Eriksson, Martin LU ; Andersson, Pär-Ola and Burman, Åke LU (1998) International ANSYS Conference In International ANSYS Conference 2. p.63-72
Abstract
All designs are marred by uncertainties and tolerances in dimen-

sions, load levels etc. Traditionally, one has often over-dimensioned

to take these uncertainties into account. The demand for optimized designs with high quality and reliability increases, which means that more sophisticated methods have been developed, see e.g. Lochner

and Matar (1990). By describing the fluctuations in design parame-

ters in terms of distributions with expectation and variance, the design can be examined with statistical methods, which results in a more op-timized design. This treatment of the design often demands several experiments, and to plan these experiments Design Of Experiments (DOE) techniques, see e.g.... (More)
All designs are marred by uncertainties and tolerances in dimen-

sions, load levels etc. Traditionally, one has often over-dimensioned

to take these uncertainties into account. The demand for optimized designs with high quality and reliability increases, which means that more sophisticated methods have been developed, see e.g. Lochner

and Matar (1990). By describing the fluctuations in design parame-

ters in terms of distributions with expectation and variance, the design can be examined with statistical methods, which results in a more op-timized design. This treatment of the design often demands several experiments, and to plan these experiments Design Of Experiments (DOE) techniques, see e.g. Montgomery (1991), are often used. By using DOE methods the design variables are systematically altered, which minimizes the number of experiments needed. The output of

the experiments is the results of a specified response function, giving

an indication of the influence of design variable fluctuations. A FEM system is a suitable tool when performing repeated, similar analyses. Examples exist where the DOE process has been performed external-

ly and then transferred to the FEM system in the form of parameter

sets defining the analysis cases that are to be solved, see e.g. Summers et al. (1996) and Billings (1996).

This paper describes a statistical DOE module based on Taguchi’s method that works within ANSYS. The module plans the FEM anal-ysis and calculates the standard statistical moments of the FEM result. This module serves as a powerful tool for the engineering designer

or analysts when examining the influence of variance and mean value of different design variables. It also serves as an exploration of where

to concentrate an optimization process. (Less)
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author
organization
publishing date
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Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
modified taguchi method, Design of experiment, Taguchi, Finite element
in
International ANSYS Conference
volume
2
pages
63 - 72
publisher
ANSYS Inc
conference name
International ANSYS Conference
language
English
LU publication?
yes
id
e89a9647-f302-4693-8523-d3f334acade8 (old id 1024333)
date added to LUP
2008-02-05 08:14:00
date last changed
2016-04-16 07:38:20
@inproceedings{e89a9647-f302-4693-8523-d3f334acade8,
  abstract     = {All designs are marred by uncertainties and tolerances in dimen-<br/><br>
sions, load levels etc. Traditionally, one has often over-dimensioned<br/><br>
to take these uncertainties into account. The demand for optimized designs with high quality and reliability increases, which means that more sophisticated methods have been developed, see e.g. Lochner<br/><br>
and Matar (1990). By describing the fluctuations in design parame-<br/><br>
ters in terms of distributions with expectation and variance, the design can be examined with statistical methods, which results in a more op-timized design. This treatment of the design often demands several experiments, and to plan these experiments Design Of Experiments (DOE) techniques, see e.g. Montgomery (1991), are often used. By using DOE methods the design variables are systematically altered, which minimizes the number of experiments needed. The output of<br/><br>
the experiments is the results of a specified response function, giving<br/><br>
an indication of the influence of design variable fluctuations. A FEM system is a suitable tool when performing repeated, similar analyses. Examples exist where the DOE process has been performed external-<br/><br>
ly and then transferred to the FEM system in the form of parameter<br/><br>
sets defining the analysis cases that are to be solved, see e.g. Summers et al. (1996) and Billings (1996).<br/><br>
This paper describes a statistical DOE module based on Taguchi’s method that works within ANSYS. The module plans the FEM anal-ysis and calculates the standard statistical moments of the FEM result. This module serves as a powerful tool for the engineering designer<br/><br>
or analysts when examining the influence of variance and mean value of different design variables. It also serves as an exploration of where<br/><br>
to concentrate an optimization process.},
  author       = {Eriksson, Martin and Andersson, Pär-Ola and Burman, Åke},
  booktitle    = {International ANSYS Conference},
  keyword      = {modified taguchi method,Design of experiment,Taguchi,Finite element},
  language     = {eng},
  pages        = {63--72},
  publisher    = {ANSYS Inc},
  title        = {Using design-of-experiments techniques for an efficient finite element study of the influence of changed parameters in design},
  volume       = {2},
  year         = {1998},
}