Subjective operational reliability assessment of maritime transportation system

Gaonkar, Rajesh S. Prabhu; Xie, Min; Ng, Kien Ming; Habibullah, Mohamed

doi:10.1016/j.eswa.2011.04.187

Cited by 12 publications

(7 citation statements)

References 22 publications

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“…The uncertainty factor could delay the operation and cause the deviation of the pre-determined plan. Therefore, the decision-maker often adjust the operation plan according to the uncertainty factors [47]. For floating production storage and offloading (FPSO), the unpredictable weather condition and vessel availability are the main reason for operation delay, and the decision-maker often leave some storage capability as the buffer for the unexpected delay [48].…”

Section: Literature Reviewmentioning

confidence: 99%

Coastal Shuttle Tanker Scheduling Model Considering Inventory Cost and System Reliability

et al. 2020

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The near-sea offshore oil extraction and transportation system use heterogeneous fleets to transfer crude oil from the floating production storage and offloading to the land-based oil storage port. Based on the characteristics of this system, the short sea inventory routing problem is investigated considering the shuttle tanker fleet and inventory management. In order to minimize the total operation cost and maximize the system reliability, a semi-continuous model for the shuttle tanker scheduling problem is established. The model optimizes the tanker scheduling plan and the design of the tanker fleet. To solve the complex model, this paper proposes an improved non-dominated sorting genetic algorithm with differential evolution operator to solve the optimization of the multi-objective model. This research also uses public vessel operation data to test the modeling and optimizing efficiency. The Pareto Fronts associated with the total operation cost and the system reliability from the optimization outcome is analyzed to provide scheduling priority advice. The results indicate that proposed optimization algorithms are effective, and the operation could be optimized with the proposed model and algorithm. INDEX TERMS Maritime inventory routing problem, non-dominated sorting genetic algorithm (NSGA-II), offshore oil transportation, semi-continuous model, shuttle tanker, system reliability.

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Section: Literature Reviewmentioning

confidence: 99%

Coastal Shuttle Tanker Scheduling Model Considering Inventory Cost and System Reliability

et al. 2020

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“…According to the ship accident data investigated by Tzannatos and Kokotos, the number of accidents is significantly reduced after the International Safety Management (ISM) Code was implemented in 1998 [13,14]. Although the maritime authorities have adopted a set of regulations and rules to regulate safety standards, these regulations or rules are not fully effective, and consequently, maritime accidents caused by human errors continue to happen and have not yet fallen to an acceptable level [15,16]. In order to reduce maritime accidents as far as possible, it is necessary to pay attention to the types of human errors [17].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Underlying Causes of Chinese Eastern Star, Korean Sewol, and Thai Phoenix Ferry Accidents by Employing the HFACS-MA

Wang¹,

Zhang²,

Zhao³

et al. 2020

IJERPH

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Maritime safety is a significant topic in the maritime industry since the numerous dangers at sea could lead to loss of property, environmental pollution, and even casualties. Existing research illustrates that human factors are the primary reasons of maritime accidents. Indeed, numerous maritime accidents can be classified into different types of human factors. In this context, the Human Factors Analysis and Classification System for Maritime Accidents (HFACS-MA) model is introduced in this paper. The HFACS-MA framework consists of five levels, complying with the core concepts of HFACS and the guiding principles of the International Maritime Organization (IMO). Based on the five levels of the framework, this research explores the underlying causes of Chinese Eastern Star, Korean Sewol, and Thai Phoenix accidents, and a comparative analysis is conducted. The analysis demonstrates the utility of applying the HFACS-MA model to the maritime industry, and the results emphasize the importance of the following categories: legislation gaps, organizational process, inadequate supervision, communication (ships and VTS), decision errors, and so on. Consequently, the research enables increased support for HFACS-MA and its application and provides valuable information for safety management and policy development in the maritime industry at different levels.

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“…Ma 3 used more accurate simulation methods to investigate the properties Nomenclature: a b b ' M 0 U, material coefficients; C, copula function; D, cumulative damage; F (t), failure probability; g(t), time-varying reliability function; N f , fatigue life; n, load cycle; R(t), degree of reliability; r(n), residual strength; S max , peak load; S P1 , first-stage loading; S P2 , second-stage loading; μ g , mean of g(t); υ, critical cycle ratio; σ max , maximum stress; σ −1 , fatigue limit; σ −1 (σ m ), fatigue limit of mean stress; σ b , initial static fatigue strength; σ g , standard deviation of g(t); 1/θ, estimated correlation parameter; d 2 Gum , squared Euclidean distance of accelerated life tests with small sample sizes where large-sample approximations may be expected to be inadequate. Gaonkar 4 established a reliability calculation model according to aggregation, the mapping of fuzzy sets using a distance measure, and a fuzzy logic rule base.…”

Section: Introductionmentioning

confidence: 99%

“…Ma used more accurate simulation methods to investigate the properties of accelerated life tests with small sample sizes where large‐sample approximations may be expected to be inadequate. Gaonkar established a reliability calculation model according to aggregation, the mapping of fuzzy sets using a distance measure, and a fuzzy logic rule base.…”

Section: Introductionmentioning

confidence: 99%

Copula‐function‐based analysis model and dynamic reliability of a gear transmission system considering failure correlations

Wei

Pan

Lin

et al. 2018

Fatigue Fract Eng Mat Struct

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In this study, an improved prediction model is introduced to assess the residual strength of gear transmission systems. The residual strength and stress‐strength interference theories are then combined to facilitate the study of the reliability of the gears and bearings in these systems. Based on the copula function, the correlation between the gear contact and bending failure is determined. The relationship between the copula function and reliability is used to determine the dynamic reliability of the gears while considering multiple correlated failure modes. In this manner, more accurate and dynamic reliability attenuation characteristics are obtained for the gear transmission system.

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Subjective operational reliability assessment of maritime transportation system

Cited by 12 publications

References 22 publications

Coastal Shuttle Tanker Scheduling Model Considering Inventory Cost and System Reliability

Coastal Shuttle Tanker Scheduling Model Considering Inventory Cost and System Reliability

Exploring the Underlying Causes of Chinese Eastern Star, Korean Sewol, and Thai Phoenix Ferry Accidents by Employing the HFACS-MA

Copula‐function‐based analysis model and dynamic reliability of a gear transmission system considering failure correlations

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