The effect of failure on energy efficiency in maritime vessels autopilot systems

IF 4.8 2区环境科学与生态学 Q1 OCEANOGRAPHY

Ocean & Coastal Management Pub Date : 2024-10-23 DOI:10.1016/j.ocecoaman.2024.107451

Hürol Hocek , Devran Yazır , Cemalettin Aygün , Ünal Özdemir

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Abstract

The increasing demands for energy efficiency and environmental sustainability in the maritime industry have underscored the critical importance of optimizing autopilot systems, which, despite their significance, are often overlooked in ship energy efficiency management. The objective of this study is to enhance the energy efficiency of ships by focusing on the efficiency of autopilot systems, which play a significant role in the management of energy efficiency. The research emphasizes the need for effective decision support systems for ship operators, not only for optimizing ship speeds but also for making informed operational decisions. By utilizing Fuzzy Fault Tree Analysis (FFTA), the study identifies and prioritizes the causes of efficiency losses in autopilot systems and examines their frequency. Based on expert opinions, the research delves into the complexity of autopilot systems and the interactions among various components. Notably, the study highlights the impact of multiple factors on the efficiency of complex autopilot systems, elucidating their relationships through Minimum Cut Sets (MCS) analysis. Furthermore, attention was drawn to the “Improper Alarm Input” event caused by insufficient knowledge and awareness among ship operators, which hinders the effective use of autopilot systems. The findings demonstrate that decision support systems can increase energy efficiency and contribute to the reduction of operational errors by reducing the human factor, which is 99% effective on the “Inefficient Heading Control System”. Additionally, proper utilization of autopilot systems can lead to a decrease in a ship's carbon footprint and operating costs. Overall, the results can affect strategic decisions in ship energy efficiency management and encourage significant steps toward achieving International Maritime Organization's (IMO) sustainability objectives.

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船舶自动驾驶系统故障对能源效率的影响

海运业对能源效率和环境可持续性的要求日益提高，这凸显了优化自动驾驶系统的极端重要性，尽管自动驾驶系统非常重要，但在船舶能源效率管理中却经常被忽视。本研究的目的是通过关注在能效管理中发挥重要作用的自动驾驶系统的效率来提高船舶能效。研究强调，船舶运营商需要有效的决策支持系统，这不仅是为了优化船速，也是为了做出明智的运营决策。通过利用模糊故障树分析法（FFTA），该研究确定了自动驾驶系统效率损失的原因和优先顺序，并检查了其发生频率。根据专家意见，研究深入探讨了自动驾驶系统的复杂性和各组件之间的相互作用。值得注意的是，研究强调了多种因素对复杂自动驾驶系统效率的影响，并通过最小割集（MCS）分析阐明了这些因素之间的关系。此外，研究还关注了由于船舶操作员知识和意识不足而导致的 "不当警报输入 "事件，这阻碍了自动驾驶系统的有效使用。研究结果表明，决策支持系统可以提高能效，并通过减少人为因素来减少操作失误，对 "低效航向控制系统 "的有效率为 99%。此外，正确使用自动驾驶系统可以减少船舶的碳足迹和运营成本。总之，研究结果可以影响船舶能效管理的战略决策，并鼓励朝着实现国际海事组织（IMO）的可持续发展目标迈出重要一步。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ocean & Coastal Management 环境科学-海洋学

CiteScore

8.50

自引率

15.20%

发文量

321

审稿时长

60 days

期刊介绍： Ocean & Coastal Management is the leading international journal dedicated to the study of all aspects of ocean and coastal management from the global to local levels. We publish rigorously peer-reviewed manuscripts from all disciplines, and inter-/trans-disciplinary and co-designed research, but all submissions must make clear the relevance to management and/or governance issues relevant to the sustainable development and conservation of oceans and coasts. Comparative studies (from sub-national to trans-national cases, and other management / policy arenas) are encouraged, as are studies that critically assess current management practices and governance approaches. Submissions involving robust analysis, development of theory, and improvement of management practice are especially welcome.