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Improving Human Reliability Analysis for railway systems using fuzzy logic
Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139, Florence, Italy.
Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139, Florence, Italy.
Department of Information Engineering, University of Florence, via di Santa Marta 3, 50139, Florence, Italy.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Industry and Transport Division, Tecnalia Research and Innovation, Miñano (Araba), 01510, Spain.ORCID iD: 0000-0002-4107-0991
2021 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 9, p. 128648-128662Article in journal (Refereed) Published
Abstract [en]

The International Union of Railway provides an annually safety report highlighting that human factor is one of the main causes of railway accidents every year. Consequently, the study of human reliability is fundamental, and it must be included within a complete reliability assessment for every railway-related system. However, currently RARA (Railway Action Reliability Assessment) is the only approach available in literature that considers human task specifically customized for railway applications. The main disadvantages of RARA are the impact of expert’s subjectivity and the difficulty of a numerical assessment for the model parameters in absence of an exhaustive error and accident database. This manuscript introduces an innovative fuzzy method for the assessment of human factor in safety-critical systems for railway applications to address the problems highlighted above. Fuzzy logic allows to simplify the assessment of the model parameters by means of linguistic variables more resemblant to human cognitive process. Moreover, it deals with uncertain and incomplete data much better than classical deterministic approach and it minimizes the subjectivity of the analyst evaluation. The output of the proposed algorithm is the result of a fuzzy interval arithmetic, α-cut theory and centroid defuzzification procedure. The proposed method has been applied to the human operations carried out on a railway signaling system. Four human tasks and two scenarios have been simulated to analyze the performance of the proposed algorithm. Finally, the results of the method are compared with the classical RARA procedure underline compliant results obtain with a simpler, less complex and more intuitive approach.

Place, publisher, year, edition, pages
IEEE, 2021. Vol. 9, p. 128648-128662
Keywords [en]
Fuzzy logic, Human factors, Reliability engineering, Railway engineering, Maintenance
National Category
Reliability and Maintenance
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-87094DOI: 10.1109/ACCESS.2021.3112527ISI: 000697811700001Scopus ID: 2-s2.0-85115180898OAI: oai:DiVA.org:ltu-87094DiVA, id: diva2:1594611
Note

Validerad;2021;Nivå 2;2021-09-28 (alebob)

Available from: 2021-09-16 Created: 2021-09-16 Last updated: 2021-12-21Bibliographically approved

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Galar, Diego

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