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2024 Journal Impact Factor - 0.6
2024 CiteScore - 1.9
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
Enhanced Predictive Diagnostics for Naval Equipment: Integrating MYT Decomposition for Advanced Process Monitoring
1 University of the Basque Country, Portugalete, Spain
2 University of Split, Split, Croatia
3 University of Cantabria, Santander, Spain
2 University of Split, Split, Croatia
3 University of Cantabria, Santander, Spain
ABSTRACT: The competitiveness in maritime operations demands maintenance strategies that ensure high reliability and availability at minimal cost. While predictive diagnostics have shown promise in detecting deviations from optimal operating conditions, current methodologies often fail to effectively isolate and identify the contributing process variables. This study introduces an enhanced predictive diagnostic approach that integrates MYT (Mason, Young, Tracy) decomposition with traditional statistical monitoring techniques, such as Hotelling's T² control charts. By applying this methodology to the auxiliary systems of a 284-meter LNG tanker, we identified that the key variables driving process anomalies were Superheated Steam in Boiler 1 (Tn/h) and Superheated Steam in Boiler 2 (Tn/h). These findings underscore the ability of the proposed method to detect deviations before critical failures occur, providing ship operators with actionable insights to enable precise maintenance scheduling, reduce operational costs, and prevent unscheduled downtime. The demonstrated integration of MYT decomposition into predictive maintenance protocols highlights its potential to optimize monitoring accuracy and decision-making in complex naval systems.
KEYWORDS: Risk Management, Maritime Industry, Marine Engineering, Operational Efficiency, Ship Maintenance, Safety of Ship Operations, Ship Systems Reliability, Harsh Operating Conditions
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Citation note:
Boullosa-Falces D., Sánchez-Varela Z., Urtaran Lavín E., Sanz D., García S.: Enhanced Predictive Diagnostics for Naval Equipment: Integrating MYT Decomposition for Advanced Process Monitoring. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 19, No. 2, doi:10.12716/1001.19.02.25, pp. 543-548, 2025
Authors in other databases:
David Boullosa-Falces:
orcid.org/0000-0002-3242-0283

Egoitz Urtaran Lavín:
orcid.org/0000-0002-9522-321X

David Salvador Sanz:
Sergio García: