Establishment of a foundation for predictive design analysis within the engineering design process
(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:
https://lup.lub.lu.se/record/1024355
- author
- Eriksson, Martin LU
- organization
- publishing date
- 2003
- 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
- conference location
- United States
- conference dates
- 2003-05-27
- language
- English
- LU publication?
- yes
- id
- 837d436f-bfd1-4aed-ae13-98c065f38b52 (old id 1024355)
- date added to LUP
- 2016-04-04 13:38:08
- date last changed
- 2018-11-21 21:15:17
@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}},
keywords = {{stochastic; Statistics; Predictive Design Analysis; Predictive Engineering; Mechanical engineering design process; Design Of Experiments}},
language = {{eng}},
title = {{Establishment of a foundation for predictive design analysis within the engineering design process}},
url = {{https://lup.lub.lu.se/search/files/6168484/1024356.pdf}},
year = {{2003}},
}