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Establishment of a foundation for predictive design analysis within the engineering design process

Eriksson, Martin LU (2003) NAFEMS WORLD CONGRESS 2003
Abstract
In today’s highly competitive

market place it is of great importance for

companies to deliver reliable products while

decreasing the development time and costs.

The time to market is a driving force for

many companies, and throughout the

engineering design process as well as the

manufacturing process, the focus is on

finding timesaving actions. However, the

search for timesaving actions will most

certainly result in a loss in product reliability

if it is not combined with improved

techniques and tools used by members of

the engineering design team in order to

maintain an acceptable level of reliability.

One... (More)
In today’s highly competitive

market place it is of great importance for

companies to deliver reliable products while

decreasing the development time and costs.

The time to market is a driving force for

many companies, and throughout the

engineering design process as well as the

manufacturing process, the focus is on

finding timesaving actions. However, the

search for timesaving actions will most

certainly result in a loss in product reliability

if it is not combined with improved

techniques and tools used by members of

the engineering design team in order to

maintain an acceptable level of reliability.

One of the areas within engineering design

that is adopting new techniques and

methodologies is the design analysis

activity that has conventionally been

performed by specialists, but has to some

extent shifted to also be performed, where

applicable, by design engineers. Further,

design analysis has traditionally been

utilized as a verification tool at the latter

engineering design phases and also for

failure mode analysis with the objective to

investigate failed designs or produce results

about whether or not it will withstand

applied loading conditions. Today both the

research community and industry perceive

the value added when design analysis is

used in early engineering design phases to

predict the performance of the product to be.

Statistically planned and Stochastic

(alternatively called in literature

probabilistic) Finite Element Analysis (FEA)

are addressed frequently in this area of

research, and different mathematical

methodologies have been discussed to

provide this value-added information within

design analysis. Fractional factorial

designed experiments, Response Surface

Methodologies (RSM) and Monte Carlo

Simulations (MCS) are among the most

commonly discussed approaches. One of

the vital issues here is the shift from the

deterministic design analysis approach, in

which accounting for variations is done

through safety factors that are overly

conservative, to a Statistical or Stochastic

design analysis approach where variables

are defined in terms of their characteristics:

the nature of the distribution of values, a

typical value, and also, in stochastic

approaches, a measure of the variability.

A presentation of Predictive Design Analysis

(PDA) is made in this paper, which

incorporates Statistical and Stochastic

approaches to perform design analysis at

different phases of the engineering design

process. The PDA methodology addresses

abounding uncertainties i.e. material

properties, magnitude and direction of

loading, part geometry as well as the issues

regarding sensitivity to variables acting on

the product in service, all of which result in

performance that is considerably different

from the ideal. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
stochastic, Statistics, Predictive Design Analysis, Predictive Engineering, Mechanical engineering design process, Design Of Experiments
pages
13 pages
conference name
NAFEMS WORLD CONGRESS 2003
language
English
LU publication?
yes
id
837d436f-bfd1-4aed-ae13-98c065f38b52 (old id 1024355)
date added to LUP
2008-02-04 12:41:37
date last changed
2016-04-16 11:28:27
@misc{837d436f-bfd1-4aed-ae13-98c065f38b52,
  abstract     = {In today’s highly competitive<br/><br>
market place it is of great importance for<br/><br>
companies to deliver reliable products while<br/><br>
decreasing the development time and costs.<br/><br>
The time to market is a driving force for<br/><br>
many companies, and throughout the<br/><br>
engineering design process as well as the<br/><br>
manufacturing process, the focus is on<br/><br>
finding timesaving actions. However, the<br/><br>
search for timesaving actions will most<br/><br>
certainly result in a loss in product reliability<br/><br>
if it is not combined with improved<br/><br>
techniques and tools used by members of<br/><br>
the engineering design team in order to<br/><br>
maintain an acceptable level of reliability.<br/><br>
One of the areas within engineering design<br/><br>
that is adopting new techniques and<br/><br>
methodologies is the design analysis<br/><br>
activity that has conventionally been<br/><br>
performed by specialists, but has to some<br/><br>
extent shifted to also be performed, where<br/><br>
applicable, by design engineers. Further,<br/><br>
design analysis has traditionally been<br/><br>
utilized as a verification tool at the latter<br/><br>
engineering design phases and also for<br/><br>
failure mode analysis with the objective to<br/><br>
investigate failed designs or produce results<br/><br>
about whether or not it will withstand<br/><br>
applied loading conditions. Today both the<br/><br>
research community and industry perceive<br/><br>
the value added when design analysis is<br/><br>
used in early engineering design phases to<br/><br>
predict the performance of the product to be.<br/><br>
Statistically planned and Stochastic<br/><br>
(alternatively called in literature<br/><br>
probabilistic) Finite Element Analysis (FEA)<br/><br>
are addressed frequently in this area of<br/><br>
research, and different mathematical<br/><br>
methodologies have been discussed to<br/><br>
provide this value-added information within<br/><br>
design analysis. Fractional factorial<br/><br>
designed experiments, Response Surface<br/><br>
Methodologies (RSM) and Monte Carlo<br/><br>
Simulations (MCS) are among the most<br/><br>
commonly discussed approaches. One of<br/><br>
the vital issues here is the shift from the<br/><br>
deterministic design analysis approach, in<br/><br>
which accounting for variations is done<br/><br>
through safety factors that are overly<br/><br>
conservative, to a Statistical or Stochastic<br/><br>
design analysis approach where variables<br/><br>
are defined in terms of their characteristics:<br/><br>
the nature of the distribution of values, a<br/><br>
typical value, and also, in stochastic<br/><br>
approaches, a measure of the variability.<br/><br>
A presentation of Predictive Design Analysis<br/><br>
(PDA) is made in this paper, which<br/><br>
incorporates Statistical and Stochastic<br/><br>
approaches to perform design analysis at<br/><br>
different phases of the engineering design<br/><br>
process. The PDA methodology addresses<br/><br>
abounding uncertainties i.e. material<br/><br>
properties, magnitude and direction of<br/><br>
loading, part geometry as well as the issues<br/><br>
regarding sensitivity to variables acting on<br/><br>
the product in service, all of which result in<br/><br>
performance that is considerably different<br/><br>
from the ideal.},
  author       = {Eriksson, Martin},
  keyword      = {stochastic,Statistics,Predictive Design Analysis,Predictive Engineering,Mechanical engineering design process,Design Of Experiments},
  language     = {eng},
  pages        = {13},
  title        = {Establishment of a foundation for predictive design analysis within the engineering design process},
  year         = {2003},
}