Sürdürülebilir Kalkınma Amaçları

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• MakaleYalnız künye2024Scopus SJRQ2/r/munzur/2169
  A fuzzy Bayesian network risk assessment model for analyzing the causes of slow-down processes in two-stroke ship main engines

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

  This paper presents a risk assessment approach for analyzing the causes of malfunction-related main engine slowdowns. A fuzzy Bayesian Network-based methodology is used to assess the factors contributing to the engine’s slow-down processes. The model addresses the complexity and uncertainty inherent in maritime operations with fuzzy sets where numerous interrelated factors can affect engine performance, and the Bayesian network to capture probabilistic dependencies. It considers various potential causes of the slow-down of ship engines that the manufacturer provides. Results demonstrate the model's ability to identify the influential factors leading to engine slow-down events and quantify the overall risk. Integrating fuzzy logic and Bayesian Networks comprehensively assesses relevant risk factors. It enables maritime stakeholders to manage engine performance and improves operational safety proactively. Findings can inform decision-makers, enabling the implementation of targeted maintenance strategies, fuel quality control measures, and crew training programs in the maritime industry.

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  AtıfScopus19·WoS17·OpenAlex18

  İncele
• MakaleAçık Erişim2019Scopus SJRQ1/r/munzur/3314
  An interval type-2 fuzzy QUALIFLEX approach to measure performance effectiveness of ballast water treatment (BWT) system on-board ship

  Demirel, Hakan; Akyuz, Emre; Celik, Erkan; Alarcin, Fuat

  Ballast water is of paramount importance for safe and efficient shipping operation since it provides ship’s strength and stability. The ballast water, on the other hand, poses serious marine ecological problems due to the non-indigenous species (NIS) carried in sea water. The International Maritime Organisation introduced International Convention for the Control and Management of Ships’ Ballast Water and Sediments (BWM Convention) to prevent the spread of harmful species from one region to another via ballast water. According to the convention, each ship must be equipped with a proper ballast water treatment system (BWTS). In this context, this paper is aimed at measuring the performance effectiveness of current BWTS used in ships. To achieve this purpose, a Qualitative Flexible (QUALIFLEX) method is used under interval type-2 fuzzy sets (IT2FSs) environment. While the QUALIFLEX handles all possible permutations of the alternatives for outranking, the IT2FSs deal with uncertainty this paper provides practical benefits to ship owners, ship’s safety inspectors, managers and marine environmentalists during decision-making progress of the BWTS settlement on-board ship.

  AtıfScopus25·OpenAlex28

  İncele
• MakaleAçık Erişim2018Scopus SJRQ1/r/munzur/3570
  A practical application of human reliability assessment for operating procedures of the emergency fire pump at ship

  Akyuz, Emre; Celik, Erkan; Celik, Metin

  This paper aims to conduct a practical application for human reliability assessment during operating procedures of an emergency fire pump on-board ship. A systematic human error prediction is performed for designated tasks during operational procedures of the emergency fire pump since human error can be regarded as one of the major factors contributing accidents at sea. Hence, human reliability performance is evaluated to enhance fire safety management in operational level on-board ship. In the paper, marine-specific error producing conditions are adopted under fuzzy sets environment. To enhance consistency of research and minimise subjectivity during expert's judgement stage, the paper is supported with a dominance factor which is used to adjust the impact level of expert's judgments in the aggregation stage of the methodology. The outcomes of the paper provide valuable contributions to the safety managers and technical superintends to monitor fire safety management and crew reliability performance.

  AtıfScopus44·WoS38·OpenAlex42

  İncele