Manifestation of uncertainty - A classification

Melanie E. Kreye*, Yee Mey Goh, Linda B. Newnes

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Different approaches of uncertainty described in literature focus on different aspects and points of the design process and offer insights on different aspects. The aim of this paper is to propose a classification of the manifestation of uncertainty describing the different points of the design process which offers a basis for a shared understanding and characterization of uncertainty. The classification consists of context uncertainty arising from the situation circumstances, data uncertainty stemming from input information or data, model uncertainty resulting from the simplifications in models, and phenomenological uncertainty connected to the outcome of the process. Each of these categories is described in detail which offers the basis for positioning the research contributions published in previous ICED conferences. The classification allows an identification of the part of the design process which is most influenced by uncertainty and activities for improvement and uncertainty reduction can be focused at this aspect. Furthermore, techniques for modeling and managing this uncertainty can be identified.

Original languageEnglish
Title of host publicationICED 11 - 18th International Conference on Engineering Design - Impacting Society Through Engineering Design
Pages96-107
Number of pages12
Publication statusPublished - 2011
Event18th International Conference on Engineering Design, ICED 11 - Copenhagen, Denmark
Duration: 15 Aug 201118 Aug 2011

Publication series

NameICED 11 - 18th International Conference on Engineering Design - Impacting Society Through Engineering Design
Volume6

Conference

Conference18th International Conference on Engineering Design, ICED 11
Country/TerritoryDenmark
CityCopenhagen
Period15/08/1118/08/11

Keywords

  • Uncertainty
  • Uncertainty classification
  • Uncertainty management

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