An improved weighted fuzzy CREAM model for quantifying human reliability in subway construction: Modeling, validation, and application
Ning Wang, Xiuli Du, Mingju Zhang, Chengshun Xu, Xinyue Lu
Abstract
Abstract On construction sites, there are many catastrophic accidents induced by human error. The fuzzy cognitive reliability and error analysis method (CREAM) is an effective method for assessing human error hazards in such a context. However, deficiencies regarding the aspects of reasonably considering the input weight, evaluation of common performance conditions (CPCs), and the rule‐based approach for fuzzy illation are frequently encountered. This paper provides an improved weighted fuzzy CREAM model. First, the reasonable weight of the CPCs is obtained by using multiple correlation analysis and evidence theory. Second, the specific evaluation rules for CPCs are established based on Chinese codes, and the membership function for each CPC level is obtained by a statistical method. The discrete basic diagram for the control mode is then transformed into a continuous fuzzy rule‐based model. On that basis, the rationality and reliability of the model are verified by four axioms. The method that introduces the weights into the calculation of the expected effects of CPCs and the reasoning of human error probability (HEP) can help evaluate the effectiveness of CPCs on human performance. The model is sensitive to the minor alterations of CPC scores and weights; the sufficiency of the data utilization and the solution domain are also verified. An exemplified application shows the rationality and validity of the new weighted fuzzy CREAM for shield tunneling human reliability analysis. This model also provides essential HEP data that can be used in hazard analysis in other engineering fields.