Abstract
Ship maintenance is one of the key processes to improve system performance and reliability onboard. Maintenance onboard ships is required to be performed in a planned manner because safe and efficient operation of a ship is very much depending on equipment reliability in operational level. A planned maintenance system (PMS), mainly supported with software, is established to monitor the maintenance implementations on board ships. This study aims to assess the effectiveness of onboard maintenance and limited with the procedures and specific softwares employed for the maintenance on board. Specifically, the process analysis approach is developed to execute the existing ship PMS phases based on four dimensions such as input, control, output, resources (ICOR). Besides the critical points to be improved in ship maintenance, this research reveals recommendations to increase the functionality of selected software in terms of workload balance, smart scheduling and safe working environment. To demonstrate the functional improvements, an illustrative case study on an auxiliary diesel generator maintenance routines are conducted. The contributions of the study are expected in both ship operations management and marine software development.
Original language | English |
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Pages (from-to) | A11-A19 |
Journal | Transactions of the Royal Institution of Naval Architects Part A: International Journal of Maritime Engineering |
Volume | 160 |
Issue number | A1 |
DOIs | |
Publication status | Published - Jan 2018 |
Bibliographical note
Publisher Copyright:© 2018: The Royal Institution of Naval Architects.
Funding
This article is produced from Master of Science Thesis entitled “Improvement of Planned Maintenance System On-Board Ships” which was executed in Maritime Transportation and Management Engineering Programme of Piri Reis University Graduate School of Science and Engineering. The authors would like to express gratitude to the Thesis Examining Committee for their constructive comments.
Funders | Funder number |
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Piri Reis University Graduate School of Science and Engineering |