@article{HawerSchoenmannReinhart2018, author = {Hawer, Sven and Sch{\"o}nmann, Alexander and Reinhart, Gunther}, title = {Guideline for the Classification and Modelling of Uncertainty and Fuzziness}, volume = {2018}, journal = {Procedia CIRP}, number = {67}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {https://doi.org/10.1016/j.procir.2017.12.175}, pages = {52 -- 57}, year = {2018}, 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.}, language = {en} }