{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T16:57:45Z","timestamp":1780937865217,"version":"3.54.1"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52474019"],"award-info":[{"award-number":["52474019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002862","name":"China University of Petroleum, Beijing","doi-asserted-by":"publisher","award":["2462024QNXZ004"],"award-info":[{"award-number":["2462024QNXZ004"]}],"id":[{"id":"10.13039\/501100002862","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reliability Engineering & System Safety"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ress.2026.112695","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T07:48:56Z","timestamp":1775720936000},"page":"112695","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["Maintenance and reliability optimization of subsea blowout preventer hydraulic systems based on mixed Weibull modeling and redundancy strategies"],"prefix":"10.1016","volume":"275","author":[{"given":"Yang","family":"Cao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengnan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ress.2026.112695_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109655","article-title":"Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments","volume":"241","author":"Liu","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109538","article-title":"Dynamic risk assessment methodology of operation process for deepwater oil and gas equipment","volume":"239","author":"Wang","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2021.108160","article-title":"Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model","volume":"218","author":"Liu","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.108889","article-title":"Supervised dynamic probabilistic risk assessment: review and comparison of methods","volume":"230","author":"Maidana","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109383","article-title":"Importance measure-based resilience management: review, methodology and perspectives on maintenance","volume":"237","author":"Dui","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2021.108225","article-title":"Mission aborting and system rescue for multi-state systems with arbitrary structure","volume":"219","author":"Levitin","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0007","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.psep.2019.04.015","article-title":"A bibliometric review of process safety and risk analysis","volume":"126","author":"Amin","year":"2019","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112695_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109538","article-title":"Dynamic risk assessment methodology of operation process for deepwater oil and gas equipment","volume":"239","author":"Wang","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111142","article-title":"Intelligent diagnosis method for early faults of electric-hydraulic control system based on residual analysis","volume":"261","author":"Kong","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109494","article-title":"Reliability analysis of subsea wellhead system subject to fatigue and degradation during service life","volume":"239","author":"Wu","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.jlp.2020.104170","article-title":"Subsea blowout preventer (BOP): design, reliability, testing, deployment, and operation and maintenance challenges","volume":"66","author":"Shafiee","year":"2020","journal-title":"J Loss Prev Process Ind"},{"key":"10.1016\/j.ress.2026.112695_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2022.111740","article-title":"Application of integrated STAMP-BN in safety analysis of subsea blowout preventer","volume":"258","author":"Meng","year":"2022","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112695_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2024.116818","article-title":"Concurrent fault diagnosis method for electric-hydraulic system: subsea blowout preventer system as a case study","volume":"294","author":"Kong","year":"2024","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112695_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.108777","article-title":"Assessment of failure rates and reliability of floating offshore wind turbines","volume":"228","author":"Li","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109485","article-title":"Failure analysis of floating offshore wind turbines with correlated failures","volume":"238","author":"Sun","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2024.119670","article-title":"Reliability analysis of DDV and SPM in BOP-based Weibull model and expand fault dataset using deep learning","volume":"314","author":"Cao","year":"2024","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112695_bib0017","article-title":"An improved adaptive gradient-based optimization algorithm for estimating the parameters of three-parameter Weibull distribution: an application of aero-engine reliability assessment","author":"Wang","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111340","article-title":"Stress-strength reliability estimation based on probability weighted moments in small sample scenario with three-parameter Weibull distribution","author":"Zou","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0019","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111062","article-title":"Development of acceptance sampling plans under time-truncated life test for verifying product reliability using weibull-percentile lifetimes","volume":"261","author":"Wu","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.108516","article-title":"Sequential bayesian inference for Weibull distribution parameters with initial hyperparameter optimization for system reliability estimation","volume":"224","author":"Shuto","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109091","article-title":"The prediction of remaining useful lifetime for the Weibull k-out-of-n load-sharing system","volume":"233","author":"Qin","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2024.119428","article-title":"A probabilistic time-dependent corrosion wastage model for offshore platforms based on reverse diffusion model","volume":"313","author":"Feng","year":"2024","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112695_bib0023","series-title":"Journal of Physics: Conference series","article-title":"Mixture Weibull probabilistic model in wind turbine power analysis","volume":"1916","author":"Indhumathy","year":"2021"},{"issue":"4","key":"10.1016\/j.ress.2026.112695_bib0024","article-title":"Mixture Weibull exponential distribution for fitting failure times data","volume":"14","author":"Alsaggf","year":"2023","journal-title":"Am Acad Sch Res J"},{"key":"10.1016\/j.ress.2026.112695_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.engfracmech.2024.110344","article-title":"Small data reliability analysis in concrete three-point bending tests: a Weibull mixture model approach based on Weibull fracture theory","volume":"309","author":"Hu","year":"2024","journal-title":"Eng Fract Mech"},{"issue":"2","key":"10.1016\/j.ress.2026.112695_bib0026","first-page":"371","article-title":"Reliability model for key components of urban rail transit train based on improved hunter-prey optimization","volume":"239","author":"Zhong","year":"2025","journal-title":"Proc Inst Mech Eng O: J Risk Reliab"},{"key":"10.1016\/j.ress.2026.112695_bib0027","series-title":"2022 13th International Conference on Reliability, Maintainability, and Safety (ICRMS)","first-page":"50","article-title":"Reliability analysis for mixture weibull distribution with progressively censored data based on stochastic expectation-maximization method","author":"Wu","year":"2022"},{"issue":"2","key":"10.1016\/j.ress.2026.112695_bib0028","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1007\/s12206-024-0113-1","article-title":"Reliability evaluation of components with multiple failure modes based on mixture Weibull distribution using expectation maximization algorithm","volume":"38","author":"Wu","year":"2024","journal-title":"J Mech Sci Technol"},{"key":"10.1016\/j.ress.2026.112695_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2023.114678","article-title":"Resilience of wave energy farms using metocean dependent failure rates and repair operations","volume":"280","author":"G\u00f6teman","year":"2023","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112695_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.scs.2025.106388","article-title":"Urban flood risk evaluation using social media data and bayesian network approach: a spatial-temporal dynamic analysis in Wuhan city, China","volume":"126","author":"Zhang","year":"2025","journal-title":"Sustain Cities Soc"},{"issue":"2","key":"10.1016\/j.ress.2026.112695_bib0031","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1108\/ECAM-06-2021-0555","article-title":"Project portfolio risk analysis with the consideration of project interdependencies","volume":"30","author":"Bai","year":"2023","journal-title":"Eng Constr Archit Manag"},{"key":"10.1016\/j.ress.2026.112695_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109459","article-title":"An object-oriented bayesian network model for the quantitative risk assessment of navigational accidents in ice-covered Arctic waters","volume":"238","author":"Fu","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0033","article-title":"Improving reliability system in radar model based on two parameters Weibull distribution","volume":"24","author":"El-Faheem","year":"2024","journal-title":"Sci Afr"},{"key":"10.1016\/j.ress.2026.112695_bib0034","article-title":"Abd El-Hafeez T. Improving the reliability performance for radar system based on Rayleigh distribution","volume":"17","author":"El-Faheem","year":"2022","journal-title":"Sci Afr"},{"key":"10.1016\/j.ress.2026.112695_bib0035","article-title":"Evaluating the system reliability of the bridge structure using the unit half-logistic geometric distribution","volume":"21","author":"Baaqeel","year":"2023","journal-title":"Sci Afr"},{"key":"10.1016\/j.ress.2026.112695_bib0036","doi-asserted-by":"crossref","first-page":"52","DOI":"10.28924\/2291-8639-22-2024-52","article-title":"Improving the performance of a series-parallel system based on gamma distribution","volume":"22","author":"Mustafa","year":"2024","journal-title":"Int J Anal Appl"},{"issue":"3","key":"10.1016\/j.ress.2026.112695_bib0037","first-page":"339","article-title":"Reliability equivalence factors for a series\u2013parallel system of components with exponentiated Weibull lifetimes","volume":"28","author":"Alghamdi","year":"2017","journal-title":"IMA J Manag Math"},{"key":"10.1016\/j.ress.2026.112695_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.108576","article-title":"Universal redundancy strategy for system reliability optimization","volume":"225","author":"Peiravi","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0039","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.ress.2016.03.010","article-title":"Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: a simulation-based optimization approach","volume":"152","author":"Guilani","year":"2016","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112695_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.108814","article-title":"Reliability analysis for multi-state systems under K-mixed redundancy strategy considering switching failure","volume":"228","author":"Liu","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"issue":"2","key":"10.1016\/j.ress.2026.112695_bib0041","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1080\/03610926.2022.2158346","article-title":"Modeling and analysis for a repairable system with multi-state components under K-mixed redundancy strategy","volume":"53","author":"Wen","year":"2024","journal-title":"Commun Stat-Theory Methods"},{"issue":"2","key":"10.1016\/j.ress.2026.112695_bib0042","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.ress.2008.02.021","article-title":"Reliability equivalence factors of a general series\u2013parallel system","volume":"94","author":"Sarhan","year":"2009","journal-title":"Reliab Eng Syst Saf"},{"issue":"2","key":"10.1016\/j.ress.2026.112695_bib0043","first-page":"111","article-title":"Reliability equivalences of a series system consists of n independent and non-identical components","volume":"7","author":"Sarhan","year":"2006","journal-title":"Int J Reliab Appl"},{"issue":"3","key":"10.1016\/j.ress.2026.112695_bib0044","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.ress.2004.07.008","article-title":"Reliability equivalence factors of a parallel system","volume":"87","author":"Sarhan","year":"2005","journal-title":"Reliab Eng Syst Saf"},{"issue":"76","key":"10.1016\/j.ress.2026.112695_bib0045","first-page":"3769","article-title":"Reliability equivalence factors of a general","volume":"6","author":"Mustafa","year":"2012","journal-title":"Appl Math Sci"},{"key":"10.1016\/j.ress.2026.112695_bib0046","first-page":"11","article-title":"An optimization method of correlation coefficient for determining a three-parameter Weibull distribution","author":"Fu","year":"1990","journal-title":"Acta Aeronaut Astronaut Sin;(China)"},{"key":"10.1016\/j.ress.2026.112695_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2020.106770","article-title":"Bayesian linear regression for surface roughness prediction","volume":"142","author":"Kong","year":"2020","journal-title":"Mech Syst Signal Process"},{"key":"10.1016\/j.ress.2026.112695_bib0048","series-title":"Pattern recognition and machine learning","author":"Bishop","year":"2006"},{"key":"10.1016\/j.ress.2026.112695_bib0049","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.isatra.2014.07.003","article-title":"Application of Petri nets to performance evaluation of subsea blowout preventer system","volume":"54","author":"Liu","year":"2015","journal-title":"ISA Trans"}],"container-title":["Reliability Engineering & System Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026005065?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026005065?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:59:08Z","timestamp":1780934348000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0951832026005065"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":49,"alternative-id":["S0951832026005065"],"URL":"https:\/\/doi.org\/10.1016\/j.ress.2026.112695","relation":{},"ISSN":["0951-8320"],"issn-type":[{"value":"0951-8320","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Maintenance and reliability optimization of subsea blowout preventer hydraulic systems based on mixed Weibull modeling and redundancy strategies","name":"articletitle","label":"Article Title"},{"value":"Reliability Engineering & System Safety","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ress.2026.112695","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112695"}}