| 47156 |
Creator |
346e7c250ea1e999b0ae8be85c1ce8c6 |
| 47156 |
Creator |
ext-d38be682457f3e0d695d2f616fbb005c |
| 47156 |
Creator |
ext-e7d4fd0261b6089c2983ea3551b15039 |
| 47156 |
Date |
2016 |
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Is Part Of |
repository |
| 47156 |
Is Part Of |
p14691760 |
| 47156 |
abstract |
Decisions related to system architecture are difficult because of fuzziness and lack
of information combined with often-conflicting objectives. We organized an industrial
workshop with the objective of choosing 5 out of 800 architectures. The first step,
the identification of selection criteria, proved to be the greatest challenge. As
a result, designers selected system architectures that did not satisfy them without
being able to explain why. It appeared that most of the difficulties faced by the
designers came from the criteria used for architecture selection. This study aims
to identify what made the selection criteria difficult to use. The audio recordings
of the workshop were transcribed and analyzed in order to identify the obstacles related
to the definition and the use of selection criteria. The analysis highlights two issues:
the interdisciplinarity of system architecture makes criteria interdependent and the
lack of information makes it impossible to define an exhaustive set of criteria. Finally,
this study provides recommendations for selecting appropriate selection criteria and
insights for future selection support tools dedicated to system architecture design. |
| 47156 |
authorList |
authors |
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status |
peerReviewed |
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volume |
30 |
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type |
AcademicArticle |
| 47156 |
type |
Article |
| 47156 |
label |
Moullec, Marie-Lise; Jankovic, Marija and Eckert, Claudia (2016). Selecting system
architecture: What a single industrial experiment can tell us about the traps to avoid
when choosing selection criteria. Artificial Intelligence for Engineering Design,
Analysis and Manufacturing, 30 pp. 250–262. |
| 47156 |
label |
Moullec, Marie-Lise; Jankovic, Marija and Eckert, Claudia (2016). Selecting system
architecture: What a single industrial experiment can tell us about the traps to avoid
when choosing selection criteria. Artificial Intelligence for Engineering Design,
Analysis and Manufacturing, 30 pp. 250–262. |
| 47156 |
Title |
Selecting system architecture: What a single industrial experiment can tell us about
the traps to avoid when choosing selection criteria |
| 47156 |
in dataset |
oro |