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STRUCTURING AND CONTEXTUALIZING HISTORICAL DATA FOR DECISION MAKING IN EARLY DEVELOPMENT

Part of: Design Support Tools

Published online by Cambridge University Press:  11 June 2020

K. V. Sigsgaard ,
J. K. Agergaard ,
C. A. Bertram ,
N. H. Mortensen ,
I. Soleymani ,
W. Khalid ,
K. B. Hansen  and
G. O. Mueller
K. V. Sigsgaard*
Affiliation:
DTU-Technical University of Denmark, Denmark
J. K. Agergaard
Affiliation:
DTU-Technical University of Denmark, Denmark
C. A. Bertram
Affiliation:
DTU-Technical University of Denmark, Denmark
N. H. Mortensen
Affiliation:
DTU-Technical University of Denmark, Denmark
I. Soleymani
Affiliation:
DTU-Technical University of Denmark, Denmark
W. Khalid
Affiliation:
DTU-Technical University of Denmark, Denmark
K. B. Hansen
Affiliation:
DTU-Technical University of Denmark, Denmark
G. O. Mueller
Affiliation:
DTU-Technical University of Denmark, Denmark
*
*krvsig@mek.dtu.dk

Abstract

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It is important to be able to compare and evaluate different solutions early in development. This paper proposes a method for structuring historical data into a data model that can support the evaluation of new design concepts. The data is contextualized by linking it to a hierarchical decomposition of existing products. Two case studies were conducted to evaluate the value of using historical data when evaluating new concepts. The cases confirm that the proposed method is useful for evaluation of new concepts.

Keywords

big data analysisdesign analysissystematic approach

Information

Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 393 - 402
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2020. Published by Cambridge University Press

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