Affiliation:
1. Department of Management Sciences, R.O.C. Military Academy, Kaohsiung 830, Taiwan
2. Graduate Institute of Technology Management, National Chung Hsing University, Taichung 402, Taiwan
Abstract
With the rapid evolution of the information age and the development of artificial intelligence, processing human cognitive information has become increasingly important. The risk-priority-number (RPN) approach is a natural language-processing method and is the most widely used risk-evaluation tool. However, the typical RPN approach cannot effectively process the various forms of human cognitive information or hesitant information provided by experts in risk assessments. In addition, it cannot process the relative-weight consideration of risk-assessment factors. In order to fully grasp the various forms of human cognitive information provided by experts during risk assessment, this paper proposes a novel Pythagorean fuzzy set–based (PFS) risk-ranking method. This method integrates the PFS and the combined compromise-solution (CoCoSo) method to handle human cognitive information in risk-assessment problems. In the numerical case study, this paper used a healthcare waste-hazards risk-assessment case to verify the validity and rationality of the proposed method for handling risk-assessment issues. The calculation results of the healthcare waste-hazards risk-assessment case are compared with the typical RPN approach, intuitionistic fuzzy set (IFS) method, PFS method, and the CoCoSo method. The numerical simulation verification results prove that the proposed method can comprehensively grasp various forms of cognitive information from experts and consider the relative weight of risk-assessment factors, providing more accurate and reasonable risk-assessment results.
Funder
National Science and Technology Council, Taiwan
Subject
Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software
Reference42 articles.
1. Fuzzy logic approach for identifying representative accident scenarios;Markowski;J. Loss Prev. Process Ind.,2018
2. Soft failure mode and effects analysis using the OWG operator and hesitant fuzzy linguistic term sets;Chang;J. Intell. Fuzzy Syst.,2018
3. A new risk assessment framework for safety in oil and gas industry: Application of FMEA and BWM based picture fuzzy MABAC;Aydin;J. Pet. Sci. Eng.,2022
4. An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method;Huang;Ann. Oper. Res.,2022
5. Anes, V., Morgado, T., Abreu, A., Calado, J., and Reis, L. (2022). Updating the FMEA approach with mitigation assessment capabilities—A case study of aircraft maintenance repairs. Appl. Sci., 12.