A Fuzzy Logic-Enhanced Risk Assessment Framework for Battery Locomotive Maintenance in Underground Coal Mines
Rattachement africain : tr, se, us. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Battery locomotives used in underground coal mining operations require continuous maintenance, and failures occurring during these operations pose significant occupational safety and health (OSH) risks. Traditional Risk Assessment Methods (TRAMs), particularly the Risk Matrix Method (RMM), often fail to capture the uncertainty and subjectivity inherent in complex mining environments. This study develops a fuzzy logic-based risk assessment framework to improve the evaluation of accident risks associated with maintenance and repair activities in battery locomotive workshops of an underground coal mine in Turkey. Two fuzzy inference models (FL-Basic and FL-Advanced) based on expert knowledge and linguistic variables were designed using Mamdani-type inference with centroid defuzzification. The mathematical formulation of the fuzzy inference and defuzzification steps is presented explicitly, and a six-step algorithm formalises the proposed framework. The rule base of FL-Advanced systematically upweights the severity dimension relative to RMM through reassignment of 16 of the 25 consequent categories. The outputs of these models were compared with RMM to analyse their effectiveness in identifying critical hazards. Application results from Karadon Hard Coal Company show that the proposed FL-Advanced model significantly reduces ambiguity, prioritises high-severity risks more realistically, and provides a more consistent decision-making structure for OSH specialists. The study highlights the advantages of fuzzy logic for modelling uncertain, incomplete, and human-dependent data in hazardous underground mining conditions.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- A Fuzzy Logic-Enhanced Risk Assessment Framework for Battery Locomotive Maintenance in Underground Coal Mines
- Date Crossref
- 28/06/2026
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
-
Çankırı Karatekin University pays non établi dans la noticeUniversité ou école supérieure
-
Zonguldak Bülent Ecevit University pays non établi dans la noticeUniversité ou école supérieure
-
Batman University Besiri OSB Vocational School pays non établi dans la noticeUniversité ou école supérieure
-
Bitlis Eren University Department of Computer Engineering pays non établi dans la noticeUniversité ou école supérieure
-
Malmö University Biofilms Research Center for Biointerfaces (BRCB) pays non établi dans la noticeUniversité ou école supérieure
-
BioSurfaces (United States) pays non établi dans la noticeEntreprise
-
Vocational School of Social Sciences pays non établi dans la noticeUniversité ou école supérieure
-
Faculty of Engineering pays non établi dans la noticeUniversité ou école supérieure
Çankırı Karatekin University, Zonguldak Bülent Ecevit University et Besiri OSB Vocational School — Batman University, avec 5 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.