Long tail uncertainty distributions in novel risk probability classification

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Abstract

Successful engineering, manufacturing, supply and service of advanced aerospace products benefits from the effective capture, predication and reduction of risk probability. Based on the analysis of the risk probability of 15,624 group wide largely unrelated enterprise risk management entries at Rolls-Royce plc., an aerospace manufacturing and service company, non-random patterns of probability in approx. 70% of aggregated risk profiles were identified, whereby approx. 40% of these exhibit long tail (leptokurtic) characteristics. Future research is recommended to identify relevant parametric risk probability variable (relationships) and to determine whether risk probability can be predicated.

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Schwabe, O., Shehab, E., & Erkoyuncu, J. (2015). Long tail uncertainty distributions in novel risk probability classification. In Procedia CIRP (Vol. 28, pp. 191–196). Elsevier B.V. https://doi.org/10.1016/j.procir.2015.04.033

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