Jeongmin Kim

Dynamic Positioning (DP) systems are widely used in offshore operations such as drilling, subsea construction, cable laying, offshore renewable energy support, and remotely operated vehicle (ROV) operations. As offshore activities become increasingly dependent on DP capability, failures in DP systems may result in operational disruption, safety concerns, and environmental exposure. Although advances in automation and redundancy have improved DP system reliability, the offshore industry continues to report DP incidents and undesired events. This paper reviews DP station-keeping events reported by the International Marine Contractors Association (IMCA) between 2018 and 2024. The reported percentages reflect descriptive compositions of voluntary submissions rather than incident rates or statistically generalizable temporal trends. The review focuses on recurring reported patterns related to thruster and propulsion failures, electrical faults, position reference problems, computer-related failures, and human factors. The review also discusses the operational and environmental implications of DP failures during offshore activities. Loss of position, reduced redundancy, and degraded vessel capability may increase the risk of collision, subsea equipment damage, operational downtime, and other offshore safety concerns. The paper also highlights the ongoing contribution of electrical and human factors to reported DP events. Finally, the paper discusses several approaches that may improve the resilience of future DP operations, including predictive maintenance, decision-support systems, and AI-based monitoring technologies. The findings suggest that DP failures should be considered not only as technical malfunctions, but also as part of a broader offshore operational and environmental risk management issue.

Maritime autonomous surface ships (MASSs) require methods for translating system-theoretic hazards into structured and traceable inputs for subsequent scenario-based safety assessment, particularly under degraded operating conditions. This study structured 92 loss scenarios (LSs) previously derived through System-Theoretic Process Analysis (STPA) into a representative scenario framework while preserving traceability to the source hazard analysis. A three-round Delphi process involving 10 domain experts was used to group the LSs, refine overlapping categories, and evaluate the resulting framework. Round 1 produced 13 provisional categories, which were consolidated in Round 2 into 10 Representative Scenario Domains (RSDs). Each LS was assigned to one primary RSD as a traceability anchor rather than as a claim of single causality, while cross-domain interactions were represented through a separate concurrent-degradation construction layer. In Round 3, all RSDs achieved median ratings of at least 4 for name appropriateness, definition clarity, and scenario fit, with agreement proportions of 0.80 to 1.00; framework-level agreement ranged from 0.80 to 0.90. The framework provides a structured intermediate layer between STPA-derived loss scenarios and subsequent safety-assessment scenario specification. The findings support expert-based content validation rather than empirical simulator effectiveness; independent reproducibility assessment and simulator-based validation therefore remain necessary subsequent steps.

Maritime Autonomous Surface Ships (MASSs) raise safety and regulatory challenges that extend beyond technical reliability. This study builds on a published system-theoretic process analysis (STPA) of degraded operations that identified 92 loss scenarios. These scenarios were reformulated into a two-round Delphi survey with 20 experts from academic, industry, seafaring, and regulatory backgrounds. Panelists rated each scenario on severity, likelihood, and detectability. To avoid rank reversal, common in the Risk Priority Number, an adjusted index was applied. Initial concordance was low (Kendall’s W = 0.07), reflecting diverse perspectives. After feedback, Round 2 reached substantial agreement (W = 0.693, χ² = 3265.42, df = 91, p < 0.001) and produced a stable Top 10. High-priority items involved propulsion and machinery, communication links, sensing, integrated control, and human–machine interaction. These risks are further exacerbated by oceanographic conditions, such as strong currents, wave-induced motions, and biofouling, which can impair propulsion efficiency and sensor accuracy. This highlights the importance of environmental resilience in MASS safety. These clusters were translated into five action bundles that addressed fallback procedures, link assurance, sensor fusion, control chain verification, and alarm governance. The findings show that Remote Operator competence and oversight are central to MASS safety. At the same time, MASSs rely on artificial intelligence systems that can fail in degraded states, for example, through reduced explainability in decision making, vulnerabilities in sensor fusion, or adversarial conditions such as fog-obscured cameras. Recognizing these AI-specific challenges highlights the need for both human oversight and resilient algorithmic design. They support explicit inclusion of Remote Operators in the STCW convention, along with watchkeeping and fatigue rules for Remote Operation Centers. This study provides a consensus-based baseline for regulatory debate, while future work should extend these insights through quantitative system modeling.

As Maritime Autonomous Surface Ships (MASS) move toward commercialization, ensuring operational safety under degraded states has emerged as a critical challenge. This study conducts a risk analysis to identify hidden hazards that may occur when MASS operate in degraded states—conditions where the ship stays within the operational environment (OE) but outside its operational design domain (ODD). The analysis applies the System-Theoretic Process Analysis (STPA) methodology, focusing on the interactions among MASS, Remote Operations Centers (ROC), and Remote Operators (ROs) as defined in the MASS code being enacted by the International Maritime Organization (IMO). STPA modeling reveals that loss of situational awareness, information asymmetry, delayed commands, and failures in inter-system coordination are primary risk factors during degraded conditions. Based on the analysis, the study identifies control actions and safety constraints to address these hazards and proposes practical safety guidelines. These findings contribute to the development of risk-based operational modes and standards to support the safe navigation of MASS, even in degraded states.

As global efforts to combat climate change intensify, offshore wind farms have emerged as scalable and sustainable solutions. However, their deployment depends heavily on the availability of specialized vessels with Dynamic Positioning (DP) systems such as Wind Turbine Installation Vessels (WTIVs) and Service Operation Vessels (SOVs). Despite their importance, long-term demand forecasting for such vessels remains underexplored, especially in South Korea. This study presents the dDP-W model, a System Dynamics (SD)-based framework that simulates the evolving demand for DP vessels under varying technological, policy, and environmental conditions. Unlike conventional methods based on historical extrapolation, the model uses feedback-driven causality and scenario-based simulations aligned with South Korea’s offshore wind roadmap (2026–2036). Three WTIV demand scenarios—baseline, optimistic, and pessimistic—were constructed based on vessel productivity and weather-related downtime. SOV demand was estimated using cumulative turbine counts and fixed vessel coverage ratios. The simulations indicate that WTIV demand peaks in the early 2030s, requiring 6 to 7 vessels depending on conditions, while SOV demand increases steadily, reaching nearly 70 vessels by 2036. These findings highlight the need for early vessel procurement, infrastructure investment, and workforce preparation. By integrating technical, logistical, and policy factors into a dynamic model, this study provides a practical decision-support tool for stakeholders in shipbuilding and offshore energy. The results offer strategic insights to address potential vessel shortages and ensure alignment with national renewable energy goals.

The introduction of MASSs, facilitated by the advancement of autonomous navigation technologies, is anticipated to lead to the emergence of new technologies, novel vessel types, and innovative job positions like remote operators at remote operation centers. The MASS Code is currently being discussed by the Maritime Safety Committee of the International Maritime Organization. This Code is expected to be adopted in the form of non-mandatory guidelines until 2025, with the goal of establishing mandatory requirements by 2028. Additionally, revisions to the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers related to crew training and qualifications are planned for adoption by 2027. These revisions will include requirements for MASS operators. This paper aims to examine the sustainable key competencies required for safe MASS operation by remote operators using the Analytic Hierarchy Process method, considering the emergence of the new profession of remote operator. Building upon the 66 knowledge, understanding, and proficiencies outlined for marine officers in the STCW Convention, the paper aims to identify the additional competencies required for remote operators and contribute to the development of a training model for the future.