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A Mixed Integer Linear Programming Model for Cost and Carbon Aware LPG Vessel Speed Optimization under Terminal Congestion Dimas Kunto Wibisono; Beny Cahyono; Semin; Muhammad Revanza Maulana
International Journal of Marine Engineering Innovation and Research Vol. 11 No. 3 (2026)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v11i3

Abstract

Port congestion has become one of the major operational challenges in LPG logistics because it increases vessel waiting time, bunker consumption, operating costs, and greenhouse gas emissions. Conventional congestion mitigation often relies on infrastructure expansion, which requires substantial investment and long implementation periods. This study aims to develop a Mixed Integer Linear Programming (MILP) model that synchronizes LPG vessel arrival with jetty availability through optimal vessel speed selection to minimize bunker costs while reducing carbon emissions. A MILP optimization model was developed using operational data from Terminal LPG Tanjung Sekong, Indonesia. The model incorporates jetty capacity, vessel schedules, sailing time, processing time, fuel consumption, bunker prices, and vessel compatibility constraints to determine whether each vessel should operate at service speed or slow-steaming speed. Results show that the proposed model reduces bunker costs by USD 46,675/month, decreases jetty waiting time by 3.26 days/month, and lowers carbon emissions by 221.7 tCO₂/month. These findings demonstrate that synchronizing vessel arrival with terminal readiness provides a practical operational alternative to infrastructure expansion while supporting maritime decarbonization.
Enhancing the Reliability of Marine Main Diesel Engines: A Review of Failure Modes, Maintenance Strategies, and Condition Monitoring Azizs Yulihantro; Semin
International Journal of Marine Engineering Innovation and Research Vol. 11 No. 3 (2026)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v11i3

Abstract

Marine main diesel engine failures remain one of the largest sources of operational risk and commercial loss in merchant shipping, with loss of propulsion consistently ranked as a top machinery casualty category and engine maintenance quality now an explicit criterion in commercial vetting regimes such as SIRE 2.0. However, existing reviews largely treat maintenance strategy selection as a generic engineering problem, without systematically linking specific failure-mode behavior to strategy assignment or consolidating condition monitoring techniques into a subsystem-specific, actionable guide; this leaves fleet operators without a unified decision tool connecting failure diagnosis, strategy selection, and monitoring technology. This review therefore aims to (1) identify the dominant failure modes and root causes of marine main diesel engines reported in the peer-reviewed literature, (2) systematize available maintenance strategies through an integrated Failure Mode and Effects Analysis-Reliability-Centered Maintenance (FMEA–RCM) decision framework that assigns each strategy to specific subsystems; and (3) map condition monitoring techniques onto main engine components to support the transition from time-based to condition-based maintenance (CBM). A narrative literature review methodology was employed, combining structured database searches (Scopus, Web of Science, Google Scholar) with backward citation tracking across 31 peer-reviewed journal articles, textbooks, international standards, and maritime authority casualty reports published between 1997 and 2025, synthesized thematically using the bathtub failure-rate model and FMEA–RCM decision logic as the integrating analytical framework. The review found that the fuel injection system, cylinder components, turbochargers, and the lubricating and cooling oil systems are the dominant contributors to main engine unreliability, with root causes concentrated in fuel and lubricant quality, thermal overload, and deferred maintenance rather than in inherent design deficiency. A hybrid maintenance architecture combining time-based tasks for age-related failure modes with CBM for randomly occurring, detectable degradation emerged as the most effective strategy, with lubricating oil analysis, thermodynamic performance monitoring, vibration analysis, and thermography constituting the principal CBM toolkit, and organizational integration into the planned maintenance system identified as the key remaining implementation barrier..