An extended CREAM model based on analytic network process under the type‐2 fuzzy environment for human reliability analysis in the high‐speed train operation

Abstract

Human error is one of the largest contributing factors to unsafe operation and accidents in high‐speed train operation. As a well‐known second‐generation human reliability analysis (HRA) technique, the cognitive reliability and error analysis method (CREAM) has been introduced to address HRA problems in various fields. Nevertheless, current CREAM models are insufficient to deal with the HRA problem that need to consider the interdependencies between the Common Performance Conditions (CPCs) and determine the weights of these CPCs, simultaneously. Hence, the purpose of this paper is to develop a hybrid HRA model by integrating CREAM, the interval type‐2 fuzzy sets, and analytic network process (ANP) to overcome this drawback. Firstly, the interval type‐2 fuzzy sets are utilized to express the highly uncertain information of CPCs. Secondly, the ANP is incorporated into the CREAM to depict the interdependencies between the CPCs and determine their weights. Furthermore, human error probability (HEP) can be calculated based on the obtained weights. Finally, an illustrative example of the HRA problem in high‐speed train operation is proposed to demonstrate the application and validity of the proposed HRA model. The results indicate that experts prefer to express their preferences by fuzzy sets rather than crisp values, and the interdependences between the CPCs can be better depicted in the proposed model.

Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network

“…In CREAM, it is considered that each CPC factor is equally important. Since this method originated in the field of nuclear industry, Theoretically, the original general efficiency conditions can not be fully applied to the characteristics of operations in the field of metallurgy industry [ 15 , 17 , 35 ]. Therefore, the CPC should assign different weights to different work natures.…”

“…Fuzzy set theory plays an important role in human reliability analysis [14]. In many references quoting CREAM, fuzzy logic is well applied to deal with uncertain information [8,[15][16][17]. Zhang et al [8] introduced fuzzy logic in order to increase the accuracy of CREAM.Chen et al [17] introduced the interval type-2 fuzzy sets to describe the uncertainty of experts' evaluation of CPC, and used ANP method to determine the weight [18].…”

An HFM‐CREAM model for the assessment of human reliability and quantification

“…For example, Ung 25 proposed a modified CREAM method to calculate HEP in oil tanker collision, which combines fault tree analysis and fuzzy Bayesian network to perform fuzzy reasoning on the CPCs. Chen et al 26 combined the CREAM model, the interval type-2 fuzzy set, and the analytic network process (ANP) to develop a hybrid HRA technique that assigns weights to the CPCs for assessing human error in the high-speed train operation. Zhang et al 27 modified the cognitive Failure Probabilities (CFP) of the CREAM using the predicted mean vote (PMV) to avoid human error in marine research.…”

Human Reliability Analysis on Fresh Fruit Bunches Sorting Workers

“…HEP is obtained from the control mode membership and the result of Bayesian network reasoning (Zhou et al, 2018). The application of the CREAM method is expanded with fuzzy to measure the reliability of operators in operating high-speed trains (Chen et al, 2021). Human Reliability Assessment (HRA) is used to improve the safety and reliability of complex socio-technical systems.…”