New SLIM Method for Human Reliability Analysis Based on Consensus Analysis and Combination Weighting

Hua Shi · Jinghui Wang · Hu‐Chen Liu · Song‐Man Wu

16 citations0/0 files storedIEEE Transactions on Automation Science and Engineering

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Risk and Safety Analysis Multi-Criteria Decision Making Human-Automation Interaction and Safety

Abstract

Human reliability analysis (HRA) is a systematic activity to identify, analyze, and reduce human failure events in complex engineering systems. As a widely-used approach in HRA, the success likelihood index method (SLIM) mainly depends on experts’ judgments for the rating and weighting of performance shaping factors (PSFs). Additionally, the estimation precision of human error probabilities (HEPs) is greatly affected by experts’ opinions and PSF weights. In this paper, an improved SLIM by integrating the minimum cost consensus method and the game theory-based combination weighting method is developed to acquire the HEPs of operational tasks under a 2-tuple linguistic environment. To facilitate consensus reaching, the missing information in task state assessment matrices of experts is filled based on their knowledge-match levels and similarity degrees. Then, a minimum cost consensus method is used to resolve the conflicts among domain experts considering individual harmony. Besides, a game theory-based combination weighting method is introduced to determine the relative weights of PSFs by integrating their subjective and objective importance. Finally, the feasibility and advantages of the proposed SLIM are validated via an empirical case concerning bunkering operation on board.Note to Practitioners—This research is motivated by a human error assessment issue during the shipboard bunkering operation. It develops a new SLIM based on the minimum cost consensus method and the game theory-based combination weighting method. The purpose of this work is to reduce high-risk human errors in the bunkering operation and enhance maritime transportation safety. Using the proposed SLIM, practitioners can handle unknown information and discrepancies in experts’ opinions and effectively quantify human errors. The application results prove the superiority of the new model. Furthermore, the proposed SLIM can be modified and applied to the socio-technical system in other industries.

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References

2014Best-worst multi-criteria decision-making method 2000A 2-tuple fuzzy linguistic representation model for computing with words 1998Cognitive Reliability and Error Analysis Method (CREAM)2012An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges 2019A Cost Consensus Metric for Consensus Reaching Processes based on a comprehensive minimum cost model 2016Connecting the linguistic hierarchy and the numerical scale for the 2-tuple linguistic model and its use to deal with hesitant unbalanced linguistic information 2008A new evaluation model for intellectual capital based on computing with linguistic variable 1990Human reliability analysis: Need, status, trends and limitations

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