Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 9

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last
Wyniki wyszukiwania
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
EN
The maritime industry plays a crucial role in the global economy, with roughly 90% of world trade being conducted through the use of merchant ships and more than a million seafarers. Despite recent efforts to improve reliability and ship structure, the heavy dependence on human performance has led to a high number of casualties in the industry. Decision errors are the primary cause of maritime accidents, with factors such as lack of situational awareness and attention deficit contributing to these errors. To address this issue, the study proposes an Ant Colony Optimization (ACO) based algorithm to design and validate a verified set of instructions for performing each daily operational task in a standardised manner. This AI-based approach can optimise the path for complex tasks, provide clear and sequential instructions, improve efficiency, and reduce the likelihood of human error by minimising personal preference and false assumptions. The proposed solution can be transformed into a globally accessible, standardised instructions manual, which can significantly contribute to minimising human error during daily operational tasks on ships.
EN
Today huge capacity sea-going vessels are propelled by mega high-powered marine diesel ‎engines, referred to as Main Engine. Turbocharging system is an integral part of large marine diesel engine plant, ‎contributing to their safety, reliability, and efficiency. Defects in the turbocharging system ‎could result in higher fuel consumption, erratic running of the Main Engine, and in the worst ‎scenario may result in the stoppage of the Main Engine at sea. An inefficient turbocharging system may also cause major damage to turbochargers, resulting in undesirable accidents out at sea. To ‎avoid such undesirable accidents and ensure smooth operations of the Main Engine, it is required to ‎address this concern. The aim of this research is to study the turbocharging system for a ‎large Main Engine using a Kongsberg engine ‎simulator. Various malfunction of the ‎Turbocharging system is considered, relevant data is collected and analysed. ‎Moreover, a Fault Tree Analysis, (FTA) is considered to identify the top undesirable event ‎which is the failure of the Main Engine. Based on the results of this study, various steps ‎are suggested to avoid failure of the Main Engine due to the defective turbocharging ‎system.‎
3
Content available A review of human error in marine engine maintenance
EN
Maritime safety involves minimizing error in all aspects of the marine system. Human error has received much importance, being responsible for about 80% of the maritime accident worldwide. Currently, more attention has been focused to reduce human error in marine engine maintenance. On-board marine engine maintenance activities are often complex, where seafarers conduct maintenance activities in various marine environmental (i.e. extreme weather, ship motions, noise, and vibration) and operational (i.e. work overload and stress) conditions. These environmental and operational conditions, in combination with generic human error tendencies, results in innumerable forms of error. There are numerous accidents that happened due to the human error during the maintenance activities of a marine engine. The most severe human error results in accidents due to is a loss of life. Moreover, there are other consequences too such as delaying the productivity of marine operations which results in the financial loss. This study reviews methods that are currently available for identifying, reporting and managing human error in marine engine maintenance. As a basis for this discussion, authors provide an overview of approaches for investigating human error, and a description of marine engine maintenance activities and environmental and operational characteristics.
EN
Dissimilar joints of AISI 430 ferritic and AISI 304L austenitic stainless steels were produced by friction stir welding process. A sound and defect-free joint was obtained at 1 mm tool offset towards the ferritic sample located in the advancing side, and at rotational and welding speeds of 560 rpm and 50 mm/min, respectively. The XRD measurements revealed the presence of approximately equal volume fractions of ferrite (51%) and austenite (49%) phases in the stir zone (SZ). The formation of low-angle grain boundaries through the occurrence of dynamic recovery along with the presence of shear texture components in both constituent phases of ferrite and austenite in the SZ approved the occurrence of continuous dynamic recrystallization throughout the evolved microstructure. Moreover, microstructural observations showed the formation of necklace structure through the microstructure of ferrite in the SZ. Taylor map approved the strain localization in the ferrite phase. Micro-hardness measurement indicated that the hardness value is increased in the SZ. The result of tensile test showed that fracture occurred from less ductile ferritic base metal.
EN
The main propulsion engine is the heart of a vessel which carries the entire load of the ship and propels to move ahead. The main engine consists of various sub-systems, the fuel oil system is the most important one. Fuel oil system provides fuel to the engine via a fuel injector mounted on the engine cylinder head. During the voyage, the main engine of a ship encounters a variation in loads and stresses due to rough weather to harsh manoeuvring, which sometimes leads to the breakdown of the main engine. Fuel oil systems are identified as one of the main reasons for engine breakdown. Many accidents happened due to the failure of the main engine fuel oil system in the last two decades. To ensure safe and reliable main propulsion engine operation, it is required to assess the reliability of a fuel oil system. However, there is a significant lack of appropriate data to develop the reliability assessment techniques for fuel oil system. This study proposes appropriate data collection and analysis procedure for the reliability assessment of a fuel oil system. Data related to Failure Running Hours (FRH) of a fuel oil system is collected from 101 experienced marine engineers through a questionnaire. The collected data processed using a box plot and analysed for a normality test. It helps to identify the generalization of the data. Moreover, this study identified failure-prone components of a fuel oil system. The collected data will help in developing reliability assessment techniques for accurate reliability analysis of a fuel oil system. The identified failure-prone components will assist in future reliability analysis and risk mitigation strategies for improving the overall safety and reliability of the shipping industry.
6
EN
Maritime transportation is the essence of international economy. Today, around ninety percent of world trade happens by maritime transportation via 50,000 merchant ships. These ships transport various types of cargo and manned by over a million mariners around the world. Majority of these ships are propelled by marine diesel engines, hereafter referred to as main engine, due to its reliability and fuel efficiency. Yet numerous accidents take place due to failure of main engine at sea, the main cause of this being inappropriate maintenance plan. To arrive at an optimal maintenance plan, it is necessary to assess the reliability of the main engine. At present the main engine on board vessels have a Planned Maintenance System (PMS), designed by the ship management companies, considering, advise of the engine manufacturers and/or ship’s chief engineers and masters. Following PMS amounts to carrying out maintenance of a main engine components at specified running hours, without taking into consideration the assessment of the health of the component/s in question. Furthermore, shipping companies have a limited technical ability to record the data properly and use them effectively. In this study, relevant data collected from various sources are analysed to identify the most appropriate failure model representing specific component. The data collected, and model developed will be very useful to assess the reliability of the marine engines and to plan the maintenance activities on-board the ship. This could lead to a decrease in the failure of marine engine, ultimately contributing to the reduction of accidents in the shipping industry.
EN
Arctic shipping involves a complex combination of inter-related factors that need to be managed correctly for operations to succeed. In this paper, the Functional Resonance Analysis Method (FRAM) is used to assess the combination of human, technical, and organizational factors that constitute a shipping operation. A methodology is presented on how to apply the FRAM to a domain, with a focus on ship navigation. The method draws on ship navigators to inform the building of the model and to learn about practical variations that must be managed to effectively navigate a ship. The Exxon Valdez case is used to illustrate the model’s utility and provide some context to the information gathered by this investigation. The functional signature of the work processes of the Exxon Valdez on the night of the grounding is presented. This shows the functional dynamics of that particular ship navigation case, and serves to illustrate how the FRAM approach can provide another perspective on the safety of complex operations.
EN
Safe operation of a merchant vessel is dependent on the reliability of the vessel’s main propulsion engine. Reliability of the main propulsion engine is interdependent on the reliability of several subsystems including lubricating oil system, fuel oil system, cooling water system and scavenge air system. Turbochargers form part of the scavenge sub system and play a vital role in the operation of the main engine. Failure of turbochargers can lead to disastrous consequences and immobilisation of the main engine. Hence due consideration need to be given to the reliability assessment of the scavenge system while assessing the reliability of the main engine. This paper presents integration of Markov model (for constant failure components) and Weibull failure model (for wearing out components) to estimate the reliability of the main propulsion engine. This integrated model will provide more realistic and practical analysis. It will serve as a useful tool to estimate the reliability of the vessel’s main propulsion engine and make efficient and effective maintenance decisions. A case study of turbocharger failure and its impact on the main engine is also discussed.
EN
Effective and efficient maintenance is essential to ensure reliability of a ship's main propulsion system, which in turn is interdependent on the reliability of a number of associated sub- systems. A primary step in evaluating the reliability of the ship's propulsion system will be to evaluate the reliability of each of the sub- system. This paper discusses the methodology adopted to quantify reliability of one of the vital sub-system viz. the lubricating oil system, and development of a model, based on Markov analysis thereof. Having developed the model, means to improve reliability of the system should be considered. The cost of the incremental reliability should be measured to evaluate cost benefits. A maintenance plan can then be devised to achieve the higher level of reliability. Similar approach could be considered to evaluate the reliability of all other sub-systems. This will finally lead to development of a model to evaluate and improve the reliability of the main propulsion system.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.