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Advisor(s)
Abstract(s)
Currently, certain maritime assets are confronted with the challenge of optimizing their performance, even when resources are limited. They strive to minimize intervention actions on equipment while upholding safety standards and acceptable performance levels. Ships, which are not yet autonomous, serve as maritime assets responsible for transporting personnel and systems. Maintaining these ships with high performance is imperative to ensuring the safety of both material and personnel. This not only prevents damage to the ships themselves but also mitigates the potential for personnel injuries and sea pollution. Organizations, scientific community, and stakeholders have been actively developing advanced systems to monitor data from ship equipment within the scope of maintenance management. This helps in preventing breakdowns and ensures real
time knowledge about the equipment's condition. These systems employ various techniques for condition control using algorithms, statistical equations, and other methodologies on the collected data. In this investigation Fuzzy Logic will be applied to data from a selected equipment. For the case study, an air compressor from an ocean patrol vessel has been selected. This air compressor plays a crucial role on Navy ships and has been chosen by the Organization's Maintenance Management Centre for monitoring working hours and operational status.
Description
Keywords
Fuzzy logic maintenance management decision process air compressor
Pedagogical Context
Citation
Publisher
Macise
CC License
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