Evaluation of the risk of pollution caused by ship operations through bow-tie-based fuzzy Bayesian network

Bayazit, Ozan; Kaptan, Mehmet

doi:10.1016/j.jclepro.2022.135386

Cited by 36 publications

(7 citation statements)

References 104 publications

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“…The practicality of getting involved in the inference process of priori knowledge, comprehensible graphical structure, and thus easily integrating into decision‐making tools make the Bayesian network method popular (Mrówczyńska et al, 2022). Therefore, Bayesian networks have been used in scientific research fields such as critical structural (Lee & Kwon, 2023), marketing (Seyedhassani et al, 2019), medical treatment (Hikal et al, 2023), nuclear power plants (Zhao et al, 2023), and marine pollution (Bayazit & Kaptan, 2023). Furthermore, Bayesian networks can be used in data mining because of their ability to demonstrate probability relations between variables besides various algorithms that enable them to learn from the data sets (Kamal & Çakır, 2022).…”

Section: Methodology Of the Studymentioning

confidence: 99%

Fuzzy Bayesian network analysis of the factors causing food losses in reefer containers

Kaptan

Bayazit

2023

J Food Process Engineering

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It is crucial to ensure food security to continue the sustainable nutrition of the world population. Food losses in the global food supply chain pose a significant risk to food security. Especially foods that require cold chain logistics are prone to deterioration and eventually food losses. Therefore, cold chain logistics processes require operational expertise and specialized equipment. Reefer (refrigerated) container is the most used cold chain transport equipment for perishable foods requiring atmospheric control. Analyzing operational and hardware-related causes and implementing relevant countermeasures are necessary to prevent food losses in reefer containers. With this motivation in the study, the relationships between the factors causing food losses in the reefer containers were evaluated qualitatively and quantitatively via the model built using the Fuzzy Bayesian network method. The findings indicate that the most critical root causes of food losses in reefer containers are excessive time off-power, inappropriate preload conditions, and refrigerant faults, respectively. Moreover, the riskiest combination of factors that causes food loss consists of excessive time-off power, refrigerant faults, and adverse weather conditions during navigation and in port. When the existing legal framework and professional practices are examined, in light of the results of the study, the following will be recommended: Establishing minimum standard and maintenance arrangements for cooling systems, ensuring safety margin in the shelf life of the foods carried in the reefer containers, making mandatory the automatic temperature recordings systems, and increasing the number of personnel specialized in product types and transportation. The study results will benefit supply chain stakeholders for process planning and implementation to mitigate the risk of food losses in reefer containers. Practical applicationsThis study examines the factors causing food losses in reefer containers from loading to discharge. The findings indicate that the most critical root causes of food losses in reefer containers are excessive time off-power, inappropriate preload conditions, and refrigerant faults, respectively. When the existing legal framework and professional practices are examined, in light of the results of the study, the following will be

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Section: Methodology Of the Studymentioning

confidence: 99%

Fuzzy Bayesian network analysis of the factors causing food losses in reefer containers

Kaptan

Bayazit

2023

J Food Process Engineering

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“…The methods used to conduct the research in the analyzed literature were the Gaussian Plume Dispersion Approach [53], dynamic method [54], ratio-matching method [56], qualitative research methodology [65], statistical tools [68], multiple criteria decision making method [82], fuzzy Bayesian network [83], instrument of questionnaires [84], system analysis [86], normative juridical legal research method [87,105], and integrated atmospheric models and health risk functions [102].…”

Section: Research Problem Referencementioning

confidence: 99%

Considerations on Prevention of Pollution from Ships in a Seaport

Đelović

2024

Sustainability

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Negative effects on the port environment can originate from ports’ hinterland, ports’ activities and operations, and from ships. According to the available literature and long-lasting experience of numerous ports presented in different sources, pollution from ships belongs to the group of environmental priorities in ports. After a theoretical introduction where the importance of ports, their development, and the challenges/risks faced by ports (with special attention to environmental risks) are analyzed, an overview of the literature from the domain of prevention of pollution from ships is presented. Based on the standard structure of the PDCA (Plan, Do, Check, Act) management cycle, in this paper, a process model of the management (sub)system of prevention of pollution from ships in a port is proposed. Key demands related to the modeled (sub)system and bases which directly determine those demands are made concrete through an analysis of a case study: the Port of Bar (Montenegro). A categorization of domains of risks of pollution from ships in the analyzed port is conducted using the Analytic Hierarchy Process (AHP) method: considerations are based on a three-level hierarchy model: “0”—goal; level “1”—criterion; and level “2”—choice. The results of the analyses show that a domain with the highest rank of risk of pollution from ships is variant (alternative) M1: unloading oil/oil derivatives from ships to tanks (and vice versa), with a composite weight of 0.5365 (53.65%). The results of considerations presented in this paper can be used in a process of optimization of the (sub)system of prevention of pollution from ships in a multipurpose port as well as a reliable base for further research in this domain.

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“…In recent years, with the rapid development of inland navigation, the number of ships and ship tonnage in inland river waters has increased year by year. Ship's domestic sewage is continuously produced and the total amount is huge, the risk of inland water environment pollution is aggravated [1][2][3][4] . As a means of transportation on the water, the ship has a wide range of accessibility, mobility and strong activity characteristics [5] .…”

Section: Introductionmentioning

confidence: 99%

Research on intelligent receiving and control technology of domestic sewage from inland waterway vessels based on Beidou positioning

Xiong,

Tian,

Zhou

et al. 2024

International Conference on Smart Transportation and City Engineering (STCE 2023)

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This paper develops an intelligent domestic sewage receiving device for ships based on BeiDou satellite navigation and positioning technology and 5G Internet of Things, and optimizes algorithms of precise positioning of ships and node detection to address the issues of low automation of sewage receiving device, difficult identification of positioning and liquid level abnormality, and low efficiency of receiving ashore that exist in the current domestic sewage of inland waterway ships. It has developed the sewage receiving ship port integrated scheduling approach, the sewage onshore transfer path planning, and the ship sewage intelligent reception control system based on Beidou+IoT technology. The goal is to complete the closed-loop monitoring process of "monitoring of sewage from ships -receiving and discharging onshore -sewage treatment and discharge", to realize the functions of high-precision monitoring of ship sewage discharge behavior and efficient scheduling and management of sewage transfer and discharge, and to contribute in the realization of the green and high-quality development of the inland waterway transportation industry.

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Evaluation of the risk of pollution caused by ship operations through bow-tie-based fuzzy Bayesian network

Cited by 36 publications

References 104 publications

Fuzzy Bayesian network analysis of the factors causing food losses in reefer containers

Fuzzy Bayesian network analysis of the factors causing food losses in reefer containers

Considerations on Prevention of Pollution from Ships in a Seaport

Research on intelligent receiving and control technology of domestic sewage from inland waterway vessels based on Beidou positioning

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