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Risk assessment for the industrial network based on interval type-2 fuzzy sets

Chao Ren (School of Economics and Management, Southeast University, Nanjing, China)
Xiaoxing Liu (School of Economics and Management, Southeast University, Nanjing, China)
Zongqing Zhang (School of Economics and Management, Southeast University, Nanjing, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 11 July 2019

Issue publication date: 20 February 2020

Abstract

Purpose

The purpose of this paper is to develop a risk evaluation method for the industrial network under high uncertain environment.

Design/methodology/approach

This paper introduces an extended safety and critical effect analysis (SCEA) method, which takes the weight of each industry in a network into risk assessment. Furthermore, expert experience and fuzzy logic are introduced for the evaluation of other parameters.

Findings

The proposed approach not only develops weight as the fifth parameter in quantitative risk assessment but also applies the interval type-2 fuzzy sets to depict the uncertainty in the risk evaluation process. The risk rating of each parameter excluding weight is determined by using the interval type-2 fuzzy numbers. The risk magnitude of each industry in the network is quantified by the extended SCEA method.

Research limitations/implications

There is less study in quantitative risk assessment in the industrial network. Additionally, fuzzy logic and expert experience are expressed in the presented approach. Moreover, different parameters can be determined by different weights in network risk assessment in the future study.

Originality/value

The extended SCEA method presents a new way to measure risk magnitude for industrial networks. The industrial network is developed in risk quantification by assessing weights of nodes as a parameter into the extended SCEA. The interval type-2 fuzzy number is introduced to model the uncertainty of risk assessment and to express the risk evaluation information from experts.

Keywords

Acknowledgements

The work is supported by the National Science Foundation of China (NSFC) (71673043).

Citation

Ren, C., Liu, X. and Zhang, Z. (2020), "Risk assessment for the industrial network based on interval type-2 fuzzy sets", Kybernetes, Vol. 49 No. 3, pp. 916-937. https://doi.org/10.1108/K-12-2018-0680

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited