Evaluation for Parachute Operator Reliability Based on Fuzzy CREAM

DOI

10.2991/mmssa-18.2019.37How to use a DOI?

Keywords

parachute; human reliability analysis; cognitive reliability and error analysis method; fuzzy theory; common performance condition

Abstract

It is important to evaluate the reliability of parachute operators before implementing the airborne mission to improve the mission completion rate and ensure the safety of personnel. This paper draws on the cognitive reliability and error analysis method (CREAM), and establishes a quantitative model of human reliability based on fuzzy CREAM for the CREAM model in which the common performance condition (CPC) describes the horizontal boundary is not obvious and the error probability interval is wide. Firstly, the CPCs of the CREAM model are modified according to the characteristics of the airborne operation, and the threshold of the performance evaluation index is clarified. Secondly, the common performance evaluation index is quantified based on the Gaussian function, and the weight of the index is assigned; Third, defuzzify the probability of error and calculate the probability of human error. The analysis of the example shows that the method considers the individual, equipment, mission, environment, organization and other factors, and has certain objectivity. It can be used for the reliability assessment of parachute operators before the mission, reducing the incidence of human error. It can also be used for reliability analysis of personnel operations in parachute system reliability assessment.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhanfeng Wang
AU  - Jianbo Wang
AU  - Dushu Li
AU  - Wenbao Dai
AU  - Qiang Zhao
PY  - 2019/01
DA  - 2019/01
TI  - Evaluation for Parachute Operator Reliability Based on Fuzzy CREAM
BT  - Proceedings of the 2018 International Conference on Mathematics, Modeling, Simulation and Statistics Application (MMSSA 2018)
PB  - Atlantis Press
SP  - 156
EP  - 159
SN  - 1951-6851
UR  - https://doi.org/10.2991/mmssa-18.2019.37
DO  - 10.2991/mmssa-18.2019.37
ID  - Wang2019/01
ER  -