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USVs are designed to undertake critical and extended missions, often in extreme conditions, without human intervention. This makes the USVs susceptible to equipment malfunction, which increases the probability of system failure during mission execution. In fact, in the absence of any crew onboard, system failure during a mission can create a great inconvenience for the concerned stakeholders, which compels them to design highly reliable USVs that must have integrated intelligent PHM systems onboard. To improve mission reliability and health management of USVs, researchers have been investigating and proposing PHM-based tools or frameworks that are claimed to operate in real time. This paper presents a comprehensive review of the existing literature on recent developments in PHM-related studies in the context of USVs. It covers a broad perspective of PHM on USVs, including system simulation, sensor data, data assimilation, data fusion, advancements in diagnosis and prognosis studies, and health management. After reviewing the literature, this study summarizes the lessons learned, identifies current gaps, and proposes a new system-level framework for developing a hybrid (offline\u2013online) optimization-based PHM system for USVs in order to overcome some of the existing challenges.<\/jats:p>","DOI":"10.1115\/1.4065483","type":"journal-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T15:23:17Z","timestamp":1715181797000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":3,"title":["Prognostics and Health Management of Unmanned Surface Vessels: Past, Present, and Future"],"prefix":"10.1115","volume":"24","author":[{"given":"Indranil","family":"Hazra","sequence":"first","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, Center for Risk and Reliability, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew J.","family":"Weiner","sequence":"additional","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, Center for Risk and Reliability, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruochen","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, Center for Risk and Reliability, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arko","family":"Chatterjee","sequence":"additional","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Southgate","sequence":"additional","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katrina M.","family":"Groth","sequence":"additional","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, Center for Risk and Reliability, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shapour","family":"Azarm","sequence":"additional","affiliation":[{"name":"University of Maryland Department of Mechanical Engineering, Center for Risk and Reliability, , College Park, MD 20742"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"33","published-online":{"date-parts":[[2024,6,3]]},"reference":[{"issue":"2","key":"2025060220020174200_CIT0001","doi-asserted-by":"publisher","first-page":"72","DOI":"10.3390\/machines10020072","article-title":"Marine Systems and Equipment Prognostics and Health Management: A Systematic Review From Health Condition Monitoring to Maintenance Strategy","volume":"10","author":"Zhang","year":"2022","journal-title":"Machines"},{"key":"2025060220020174200_CIT0002","first-page":"6461","article-title":"Development of an Information Fusion System for Engine Diagnostics and Health Management","author":"Volponi","year":"2004"},{"key":"2025060220020174200_CIT0003","first-page":"2195","article-title":"Automatic Fault Detection for Marine Diesel Engine Degradation in Autonomous Ferry Crossing Operation","author":"Ellefsen","year":"2019"},{"key":"2025060220020174200_CIT0004","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.isatra.2021.02.024","article-title":"A Bayesian Inference-Based Approach for Performance Prognostics Towards Uncertainty Quantification and Its Applications on the Marine Diesel Engine","volume":"118","author":"Wang","year":"2021","journal-title":"ISA Trans."},{"key":"2025060220020174200_CIT0005","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.rser.2018.09.012","article-title":"Deep Learning for Fault Detection in Wind Turbines","volume":"98","author":"Helbing","year":"2018","journal-title":"Renew. 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