Guideline for the Classification and Modelling of Uncertainty and Fuzziness

Sven Hawer, Alexander Schönmann, Gunther Reinhart

Research output: Contribution to journalConference articlepeer-review

17 Scopus citations

Abstract

Methods for managing uncertainty and fuzziness caused by a turbulent and volatile corporate environment play an important role for ensuring long-term competitiveness of producing companies. It is often difficult for practitioners, to choose the optimal approach for modelling existing uncertainties in a meaningful way. This contribution provides a guideline for classification of uncertain information and fuzzy data based on a flowchart and proposes suitable modelling methods for each characterized uncertainty. In addition, a measure for modelability, the degree to which an uncertain or fuzzy parameter can be modelled, is proposed. The method is based on a literature review comprising a discussion of the terms uncertainty and fuzziness.

Original languageEnglish
Pages (from-to)52-57
Number of pages6
JournalProcedia CIRP
Volume67
DOIs
StatePublished - 2018
Event11th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2017 - Ischia, Naples, Italy
Duration: 19 Jul 201721 Jul 2017

Keywords

  • Classification
  • Fuzziness
  • Modelling
  • Probability theory
  • Uncertainty

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