Revolutionizing Maintenance Strategy of Bangladesh Marine Fleet through AI-BasedConfiguration Management Software: A Design, Validation, and Implementation Pathway

Author: Dr. Khandakar Akhter Hossain, Md Hanif Mahmood, Mohammad Alamgir Hossain, Robin Islam, Md Sazzad Hossain, Md. Abu Sufian, Md. Sarjil Mehedi, Shimanto Nandi Akash, Mohammad Mahbubur Rahman, Khan Md. Mahboba Alahi
DOI: doi.org/10.70279/bmj-v3-1013

The maritime industry operates more than 80 percent of worldwide trade, but its aging fleets create growing difficulties for maintenance work. Emerging economies such as Bangladesh face challenges because their systems rely on time-based maintenance for equipment upkeep, leading to high costs and unpredictable work schedules. The research introduces the Integrated Digital Configuration Management System, which combines three maintenance methods Condition-Based Maintenance and Reliability-Centred Maintenance and Artificial Intelligence technology. The framework achieves validation through an empirical case study on marine turbocharger failures which uses the Crow-AMSAA reliability model to demonstrate a 33.9% reduction in annual maintenance costs and a 114% improvement in Mean Time Between Failures (MTBF) and provides a detailed AI integration pathway for transitioning to predictive maintenance. The reliability analysis process revealed that the system performance changed from an unstable condition with a shape parameter of 0.910 to a stable state with a shape parameter of 0.660. The Monte Carlo simulation produced results with 95% confidence intervals which validated a 16-step implementation roadmap that enables sustainable fleet modernization.