A Development of Remote Ship Maintenance System Based on Ship Area Network

Moon, Daekeun; Bae, Jeong-Yeon; Park, Jun‐Hee; Lee, Kwang; Kim, Hagbae

doi:10.3744/snak.2010.47.5.751

Cited by 4 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unlike other transportation, such as land vehicles, airplanes, and small ships, large ships operate for a long period of time, so sudden faults in rotating machines can lead to inoperability and are difficult to repair immediately. These problems lead to large economic losses, about USD 900,000, which is more than 10% of the operating costs of a 4000 TEU (twenty-foot equivalent unit) container ship, including the cost of replacing materials for ship maintenance and the cost of support staff [10].…”

Section: Introductionmentioning

confidence: 99%

Fault Simulating Test Bed for Developing Diagnostic Algorithm of the Geared Rotating Machinery of Ships

Kim,

Song

et al. 2024

JMSE

View full text Add to dashboard Cite

To prevent critical failure of the functional machinery of a ship, condition monitoring technologies have been much studied in recent times. In this respect, securing a fault database is a top priority in technology development. In this paper, we developed a test bed that simulates the LNG (liquefied natural gas) re-liquefaction system installed on LNG carriers to obtain data in various types of faults of ship machinery. To maintain rotor-dynamics characteristics, the structure was scaled based on the critical speed margin of the dynamic system. The developed test bed includes a gearbox and multiple shafts. It can simulate mass imbalance, misalignment, bearing fault, gear fault and impeller fault. To verify the validity of the vibration data obtained from the developed test bed, experiments were conducted on three fault modes: main shaft imbalance, pinion shaft imbalance, and gear fault. The time series data and FFT results were analyzed, and time domain features were extracted and statistically validated. Additionally, a simple diagnosis model was developed using the acquired data to evaluate its performance. The test data show distinct data with respect to fault conditions, and we can expect that the diagnosis algorithm can be developed using the test data. The developed test bed can provide not only for the fault data of a single component of the rotating machine but also for the combined fault data of the total system. In addition, we expect that it will solve the problem of securing fault data in the development of condition diagnosis technology if reliability is verified by identifying correlations by comparing data from the real system and data from the scaled test bed.

show abstract

Section: Introductionmentioning

confidence: 99%

Fault Simulating Test Bed for Developing Diagnostic Algorithm of the Geared Rotating Machinery of Ships

Kim,

Song

et al. 2024

JMSE

View full text Add to dashboard Cite

show abstract

“…

…”

mentioning

confidence: 99%

Maintenance Work Packaging-Based Augmented Reality Remote Maintenance Considering Maritime Network Environment

Kim,

Lee,

Kim

et al. 2023

International Conference on Civil Engineering Fundamentals and Applications

View full text Add to dashboard Cite

With the growing interest in autonomous ships, the demand for ship automation is accelerating in the shipbuilding industry [1]. Owing to such technological developments, the number of sailors aboard ships will gradually decrease. Moreover, as more experienced sailors prefer to work on land, sailors aboard ships will find it increasingly difficult to gain expertise. This results in novice sailors who are unacquainted with automation systems feeling overwhelmed by their work.Additionally, many resources and equipment are required for ships, and the cost of maintenance work accounts for 60 to 70% of the total operating cost [2,3]. Such high costs are attributed to difficulties in accessing ships at sea and the increased waiting time associated with temporarily halted operations. If the maintenance work on a ship can be quickly performed, the ship will not stop, and the stability of its operations will increase. Furthermore, the costs of simply replacing damaged parts can reach 70% of the total maintenance cost [3], making it essential to find alternative policies that can reduce maintenance costs. Accordingly, many studies have been conducted on the design and development of mobile-based real-time maintenance support tools and applications to prevent unnecessary errors [4]. Moreover, owing to the rapid development of augmented reality (AR), more studies exploiting the advantages in visualizing engineering data during maintenance work are being conducted [5]. These trending technologies contribute greatly to the development of remote maintenance support systems.Although these technologies show a good performance in terms of data visualization, experts are still crucial in situations wherein errors occur, and the necessary data for maintenance systems are absent. Additionally, even if remote support is available, receiving it is difficult owing to the instability of communication in the maritime environment. Therefore, in this study, we propose a maintenance work packaging (MWP) system to smoothly support the decision-making of sailors involved in maintenance work and also propose a maintenance plan to be implemented according to the communication environment. MWP is a planned and feasible work process involving the definition of error code, maintenance plan, excution that are implemented from the initial plan of a project to the course of its execution, and it is an effective method for systematic and efficient maintenance management. Additionally, we developed a real industrial scenario to test the proposed MWP system and conducted a functional test to determine whether the developed application could perform all the necessary functions. Finally, to verify the financial feasibility of the proposed system, we assumed a ship communication environment and calculated and analysed the associated costs.

show abstract