Guideline for the Classification and Modelling of Uncertainty and Fuzziness
- 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.
Author: | Sven Hawer, Alexander SchönmannORCiD, Gunther Reinhart |
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Language: | English |
Document Type: | Article |
Conference: | 11th CIRP Conference on Intelligent Computation in Manufacturing Engineering, Gulf of Naples (Italy), 19.-21.07.2017 |
Year of first Publication: | 2018 |
published in (English): | Procedia CIRP |
Publisher: | Elsevier |
Place of publication: | Amsterdam |
ISSN: | 2212-8271 |
Volume: | 2018 |
Issue: | 67 |
First Page: | 52 |
Last Page: | 57 |
Review: | peer-review |
Open Access: | ja |
Version: | published |
Tag: | Classification; Fuzziness; Modelling; Probability theory; Uncertainty |
URN: | urn:nbn:de:bvb:573-33572 |
Related Identifier: | https://doi.org/10.1016/j.procir.2017.12.175 |
Licence (German): | Creative Commons BY-NC-ND 4.0 |
Release Date: | 2023/04/03 |