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• MakaleYalnız künye2024Scopus SJRQ1/r/munzur/2115
  A comprehensive risk assessment framework for mooring risks at hydrocarbon berths using fuzzy rule-based Bayesian network and multi-attribute decision-making

  Demirel, Hakan; Başhan, Veysi; Yucesan, Melih; Gul, Muhammet

  Mooring operations -especially at hydrocarbon berths- are critical components of the marine and offshore industry. They usually involve securing the berths of ships carrying valuable cargo and ensuring the safety of personnel, assets, and the environment. For this purpose, a comprehensive risk assessment framework for mooring operations at hydrocarbon berths is proposed in this study. This framework helps evaluate risks using a rule-based Bayesian network. In the assessment of mooring risks, four risk parameters of severity, occurrence, detection, and maintenance are considered to construct the BN structure of each mooring risk. These parameters are weighted with the aid of the fuzzy Best Worst Method. Hereafter, a fuzzy rule-based system is constructed by incorporating BN to determine a risk priority score. The framework also develops mitigation strategies to maintain effective risk management for safe and secure maritime transportation. Sensitivity analyzes and comparison studies were conducted to test the validity of the proposed comprehensive risk management framework. The study reveals that the most critical risk is associated with Technical Failures (Q1) in the cluster pertaining to the automation of Quick Release Hooks. This risk stems from technical malfunctions in automation systems, encompassing sensors and control mechanisms, potentially resulting in the unintended release of mooring lines. The second highest priority risk is linked to Human Error (M1) in the mooring risks cluster, attributed to human errors such as inadequate training, miscommunication, and procedural mistakes during mooring operations, posing risks of accidents and damage to ships and infrastructure. Conversely, the least significant risk, Redundancy (Q5), focuses on redundancy. This risk is associated with automation and underscores the importance of implementing redundancy mechanisms to ensure the safe continuation of mooring operations in the face of system failures. In conclusion, the proposed comprehensive risk assessment framework offers a systematic approach to evaluate and prioritize mooring risks at hydrocarbon berths. The study’s findings emphasize the critical importance of addressing technical malfunctions in the automation of Quick Release Hooks and human errors during mooring operations. By identifying the most significant risks and developing mitigation strategies, this framework contributes to enhancing the safety and security of maritime transportation, particularly in the context of hydrocarbon berths.

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  AtıfScopus11·WoS11·OpenAlex13

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• MakaleYalnız künye2022Scopus SJRQ1/r/munzur/2528
  Occupational health, safety and environmental risk assessment in textile production industry through a Bayesian BWM-VIKOR approach

  Ak, M. Fatih; Yucesan, Melih; Gul, Muhammet

  Occupational risk assessment (ORA) is a process that consists of evaluating, ranking, and classifying the hazards and associated risks arising in any workplace from the viewpoint of occupational health and safety. Many ORA methods have been proposed in the literature, from a single independent expert to participatory methodologies made by group decision and simple to complex ones. In this paper, a holistic ORA is presented, which uses two important multi-attribute decision methods named Bayesian Best-Worst Method (Bayesian BWM) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Bayesian BWM is used to determine the importance weights of six different assessment criteria, which are the probability of hazardous event (P), frequency (F), severity (S), detectability (D), cost (C) and sensitivity not to use personal protective equipment (SNP). Since the classical BWM finds solution to the weights of a number of criteria from only one expert's judgment, Bayesian BWM is preferred in this paper (1) to enable participation of a group of experts, (2) to aggregate the preferences of these multiple experts into consensus without loss of information and (3) to follow a probabilistic way for solving the ORA problem. The hazards are then ranked by VIKOR. The approach is implemented in the ORA process of a textile production plant. Results of risk analysis showed that electricity hazard and associated risks constitute the highest risk ratings. These hazards arise from the product, process, human and working environment. The associated risks are evaluated, prioritized, and detailed control measures are proposed. This study made comparisons with the classical BWM-VIKOR approach to demonstrate the proposed approach's difference and practicality. Results can also help practitioners and risk analysts in formulating the improvement measures to increase the overall safety of the working environment further.

  AtıfScopus87·WoS78·OpenAlex87

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• MakaleYalnız künye2020Scopus SJRQ1/r/munzur/3763
  Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA

  Gul, Muhammet; Ak, M. Fatih

  Occupational safety issues encountered in the worksite environment are the issues that companies should consider in improving their operations with a view to human health and environmental awareness. Many methods with different rationales have been existed in the literature to prioritize hazards according to their risk levels and to mitigate their consequences. In this study, a new model is developed for occupational risk assessment by merging two well-known multi-criteria decision-making methods named best and worst method (BWM) and multi attribute ideal real comparative analysis (MAIRCA) under fuzzy environment. The proposed model differentiates from other similar models by three aspects. First, it considers severity of a hazard and its associated risk from the human and environmental riskiness perspectives. Secondly, it applies fuzzy BWM (F-BWM) to calculate the relative importance of three risk factors named as “probability, frequency and severity” of traditional Fine–Kinney method. Thirdly, it applies fuzzy MAIRCA (F-MAIRCA) to rank hazards according to their risk level using importance values obtained by F-BWM. To show applicability of the approach, a case study of risk assessment in a marble factory is fulfilled. Additionally, a number of validation studies including benchmarking analysis with fuzzy VIKOR and fuzzy TOPSIS methods; a sensitivity analysis by varying importance weights of risk factors are carried out to highlight the solidity of the proposed approach.

  AtıfScopus80·WoS70

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