Osman Turan

Analytical investigation of marine casualties at the Strait of Istanbul with SWOT–AHP method

The Strait of Istanbul is one of the most dangerous and busiest sea passages, according to its narrowness, sharp turns, currents, heavy traffic and many other important factors. Despite the latest precautions, marine incidents still occur, especially in narrow seaways. This study shows that a management tool that is specifically applied for reducing marine casualties and consequently enhancement of safety and ship management performance can be used to prevent accidents and casualties in maritime transportation. In this study, factors which affect marine casualties examined and determined with SWOT (strengths, weaknesses, opportunities and threats) analysis method and weighting of the factors determined by using the AHP (analytic hierarchy process) method. With this approach, strategic action plans were developed for minimizing shipping casualties at the Strait of Istanbul, taking into account the weighting factors and previously happened accidents.

Maintenance/repair and production-oriented life cycle cost/earning model for ship structural optimisation during conceptual design stage

The aim of this paper is to investigate the effect of the change in structural weight due to optimisation experiments on life cycle cost and earning elements using the life cycle cost/earning model, which was developed for structure optimisation. The relation between structural variables and relevant cost/earning elements are explored and discussed in detail. The developed model is restricted to the relevant life cycle cost and earning elements, namely production cost, periodic maintenance cost, fuel oil cost, operational earning and dismantling earning. Therefore it is important to emphasise here that the cost/earning figure calculated through the developed methodology will not be a full life cycle cost/earning value for a subject vessel, but will be the relevant life cycle cost/earning value. As one of the main focuses of this paper is the maintenance/repair issue, the data was collected from a number of ship operators and was solely used for the purpose of regression analysis. An illustrative example for a chemical tanker is provided to show the applicability of the proposed approach.

Increasing ship operational reliability through the implementation of a holistic maintenance management strategy

Ship maintenance was initially considered as more of a financial burden than as a way to preserve safety, environment and quality transportation. The benefits from applying a sound and systematic maintenance policy are emerging both in the minimisation of unnecessary downtime as well as in the increase of operational capability. In this paper, a novel predictive maintenance strategy is demonstrated, combining the existing ship operational and maintenance tasks with the advances stemming from new applied techniques. The initial step for the application of the above-mentioned strategy is also shown regarding the machinery space of a cruise ship. Well-known tools are applied such as Failure Modes, Effects and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA). Outcomes of this study are the identification of the critical components of the system, the estimation of the reliability of the overall system and sub-systems, the prioritisation of the maintenance tasks and finally the availability of the specific end events/items.

Susceptibility to seasickness

This paper explains part of the observed variability in passenger illness ratings aboard ships by gender, age and sickness history. Within the framework of a European project, 2840 questionnaires, gathered on several ships operating all over Europe, were analysed. Gender, age and sickness history all had a highly significant effect on seasickness. Furthermore, these effects could be characterized by two fixed parameters describing a general age effect, a third parameter dependent on sickness history and a fourth parameter dependent on gender. Female illness ratings peaked at an age of 11 years, 1.5 times as high as male ratings, which peaked at an age of 21 years. At higher ages, illness ratings decrease to only 20% of their maximum, reducing gender differences to zero. Passengers with a previous history of seasickness rated their illness about two times higher than those who had not felt sick before.

Human reliability analysis—Taxonomy and praxes of human entropy boundary conditions for marine and offshore applications

This is the first stage towards the development of a human reliability model called human entropy (HENT). The paper presents qualitative and quantitative taxonomies and praxes of performance shaping factors (PSF) for Marine and Offshore operations. Three structured and guided expert elicitation methods were used in this study. The experts interrogated accident reports and databases from which the generic root causes of failures/accidents in operations are determined. The elicitations led to the development of 9 qualitative and quantitative human influencing factors, which are called Human Entropy Boundary Conditions (HEBC). Further explications of the 9 HEBC gave birth to 137 quantifiable explanatory variables, which are called hypothetical constructs (HyC). The HyCs are used to identify potential risks due to shrinkages in safety standards. Human entropy is a detour from traditional human error and was used as a result of tripartite human failure modes; error, local rationality and extraneous acts, all of which signify disorderliness and are seemingly inevitable in maritime operations. The praxes and scaling of HEBC was developed as guidance towards a practical oriented HRA and provide inputs for measuring human disorderliness in maritime operations.

Investigating the reliability and criticality of the maintenance characteristics of a diving support vessel

Maintenance tasks and their application in the shipping industry have evolved significantly in the recent years. Particularly in the offshore industry, safety onboard, environmental protection and intensive operational activities necessitate the minimization of down-time and the preservation of an excellent performance ratio. The first step of an innovative ship maintenance strategy, which is proposed by the authors and is based on criticality and reliability assessment, is presented herein using the FTA tool with time-dependant dynamic gates so as to represent in an accurate and comprehensive way the interrelation of the components of a system. The paper also presents a review of the maintenance standards and procedures, such as the ALARP concept, the Key Programme 3-Asset Integrity (KP3) initiative, the OREDA handbook as well as the RCM and RBI principles. As part of the reliability assessment, the Birnbaum and Criticality reliability importance measures are utilized to validate the results of the analysis. A case study of a diving support vessel (DSV) illustrates the application of this strategy. The main systems examined are: the vessels power plant, propulsion, water system, lifting, hauling and anchoring, diving and finally the safety system. The reliability of the main systems and subsystems as well as of their critical components is identified and suggestions of how to improve the overall reliability of the various systems both at a component, system and managerial level are also proposed.

Investigation of Optimum Crew Transfer Vessel Fleet for Offshore Wind Farm Maintenance Operations

The offshore wind industry, which aims to reduce the operational costs, usually achieved through learning curves and supply chain improvements, has seen drastic cost increase over the last five years. In order to sustain the competitiveness of the offshore wind industry against other renewable energy sources, the cost of offshore wind needs to come down to todays onshore cost. This cost reduction target can be achieved through optimising the offshore related operations which contribute the most to the operating expenditures (OPEX) of the offshore wind farms. In this paper, the investigation of optimum crew transfer vessel fleet, which indicates the influence of fleet size and characteristics of the vessels involved in the operations, is introduced with a focus on power production, total cost of the Operation and Maintenance (O&M) and revenue loss. A time domain Monte-Carlo approach is adopted while taking into consideration the climate parameters, failure characteristics of turbine components, the specification of crew transfer vessels, and the composition of vessel fleet. Through this extensive study, it is concluded the O&M related costs can be reduced significantly while the availability and the productivity of the turbines can be increased by optimising the use of the O&M vessel fleet in terms of fleet size and vessel capabilities.

Ship-to-Ship Interaction During Overtaking Operation in Shallow Water

Hydrodynamic interaction continues to be a major contributory factor in marine casualties and hazardous incidents, in particular, in the case of overtaking operations. The situation becomes even worse when the overtaking operation occurs in shallow and narrow channels, where the interaction can cause the vessels to collide and, in one case has caused the capsizal of the smaller vessel with loss of life. The aim of this article is to propose a methodology, as well as to discuss the development of a numerical program, to predict the ship-to-ship interaction during overtaking operations in shallow water. Since the vessels involved in this study have different forward speeds, an uncoupled method will be used to solve the boundary value problem. The in-house multibody hydrodynamic interaction program MHydro, which is based on the 3D Rankine source method, is used and extended here to investigate the interactive forces and wave patterns between two ships during an overtaking operation. The calculations given in this article are compared with model test results as well as published computational fluid dynamics (CFD) calculations. Very satisfactory agreement has been obtained, which indicates that the proposed methodology and developed program are successfully validated to predict the hydrodynamic interaction between two ships advancing in confined waters. The discussions also highlight the speed effects.

Optimizing Ship Routing to Maximize Fleet Revenue at Danaos

In this paper we present an innovative toolkit that Danaos Corporation developed and deployed to optimize ship routing. Operations Research In Ship MAnagement ORISMA provides a clear answer to the conventional dilemma of least-cost voyage versus faster voyage. ORISMA maximizes revenue by using relevant information, including financial data, hydrodynamic models, weather conditions, and marketing forecasts. It considers the financial benefits after ship voyage completion to optimize the fleetwide performance instead of single-vessel performance. Using operations research and expert knowledge, we developed ORISMA to include world-class capabilities in scheduling optimization, intelligent voyage planning, ship bunkering, and chartering. In addition to maximizing Danaos’ profit, it helps the company to minimize carbon emissions, reduce staff workload, and increase customer satisfaction.

Learning-based ship design optimization approach

With the development of computer applications in ship design, optimization, as a powerful approach, has been widely used in the design and analysis process. However, the running time, which often varies from several weeks to months in the current computing environment, has been a bottleneck problem for optimization applications, particularly in the structural design of ships. To speed up the optimization process and adjust the complex design environment, ship designers usually rely on their personal experience to assist the design work. However, traditional experience, which largely depends on the designers personal skills, often makes the design quality very sensitive to the experience and decreases the robustness of the final design. This paper proposes a new machine-learning-based ship design optimization approach, which uses machine learning as an effective tool to give direction to optimization and improves the adaptability of optimization to the dynamic design environment. The natural human learning process is introduced into the optimization procedure to improve the efficiency of the algorithm. Q-learning, as an approach of reinforcement learning, is utilized to realize the learning function in the optimization process. The multi-objective particle swarm optimization method, multi-agent system, and CAE software are used to build an integrated optimization system. A bulk carrier structural design optimization was performed as a case study to evaluate the suitability of this method for real-world application.