Joint optimization of mission aborts and allocation of standby components considering mission loss
•Dynamic mission abort and components allocation policies are developed;•Mission reliability and system survivability are evaluated under the proposed policies;•Joint optimization model is established to find the optimal abort and allocation policies Mission abort is an effective way to enhance syst...
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Veröffentlicht in: | Reliability engineering & system safety 2022-09, Vol.225, p.108612, Article 108612 |
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creator | Zhao, Xian Dai, Ying Qiu, Qingan Wu, Yaguang |
description | •Dynamic mission abort and components allocation policies are developed;•Mission reliability and system survivability are evaluated under the proposed policies;•Joint optimization model is established to find the optimal abort and allocation policies
Mission abort is an effective way to enhance system safety during mission execution. Existing multi-attempt mission abort models can be divided into two main categories according to the additivity of completed missions: non-accumulative models and completely cumulative models. This paper studies the optimal mission abort and allocation of standby components policies for the k-out-of-(n+m):F system considering partial mission loss. During each attempt, the mission abort decision is dynamically controlled via predetermined abort thresholds and the rescue procedure (RP) starts immediately upon mission abort. In most studies, after a successful RP, the system is commonly restored to an ‘as good as new’ state with the underlying assumption that the standby components are always adequate. However, due to factors such as cost and capacity, the number of standby components may be limited. This paper proposes a dynamic allocation policy of a fixed number of standby components. The aim is to determine the optimal number of the failed components be replaced after each RP. By using a recursive algorithm, mission reliability and system survivability are derived. The objective is to minimize the expected cost and balance the mission reliability and the system survivability. The advantage of the proposed policy is justified by the policy comparison. Finally, the obtained results are demonstrated considering an autonomous underwater vehicle performing a photography mission. |
doi_str_mv | 10.1016/j.ress.2022.108612 |
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Mission abort is an effective way to enhance system safety during mission execution. Existing multi-attempt mission abort models can be divided into two main categories according to the additivity of completed missions: non-accumulative models and completely cumulative models. This paper studies the optimal mission abort and allocation of standby components policies for the k-out-of-(n+m):F system considering partial mission loss. During each attempt, the mission abort decision is dynamically controlled via predetermined abort thresholds and the rescue procedure (RP) starts immediately upon mission abort. In most studies, after a successful RP, the system is commonly restored to an ‘as good as new’ state with the underlying assumption that the standby components are always adequate. However, due to factors such as cost and capacity, the number of standby components may be limited. This paper proposes a dynamic allocation policy of a fixed number of standby components. The aim is to determine the optimal number of the failed components be replaced after each RP. By using a recursive algorithm, mission reliability and system survivability are derived. The objective is to minimize the expected cost and balance the mission reliability and the system survivability. The advantage of the proposed policy is justified by the policy comparison. Finally, the obtained results are demonstrated considering an autonomous underwater vehicle performing a photography mission.</description><identifier>ISSN: 0951-8320</identifier><identifier>EISSN: 1879-0836</identifier><identifier>DOI: 10.1016/j.ress.2022.108612</identifier><language>eng</language><publisher>Barking: Elsevier Ltd</publisher><subject>Algorithms ; Allocation of standby components ; Autonomous underwater vehicles ; Mission abort ; Mission reliability ; Optimization ; Partial replacement ; Photography ; Reliability engineering ; Survivability ; System reliability ; System survivability ; Underwater photography ; Underwater vehicles</subject><ispartof>Reliability engineering & system safety, 2022-09, Vol.225, p.108612, Article 108612</ispartof><rights>2022</rights><rights>Copyright Elsevier BV Sep 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c258t-97e41d7fb9e3e5cc7efd3b4afb9d4ca9f4c83ab405072878761909458c140bd13</citedby><cites>FETCH-LOGICAL-c258t-97e41d7fb9e3e5cc7efd3b4afb9d4ca9f4c83ab405072878761909458c140bd13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ress.2022.108612$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Zhao, Xian</creatorcontrib><creatorcontrib>Dai, Ying</creatorcontrib><creatorcontrib>Qiu, Qingan</creatorcontrib><creatorcontrib>Wu, Yaguang</creatorcontrib><title>Joint optimization of mission aborts and allocation of standby components considering mission loss</title><title>Reliability engineering & system safety</title><description>•Dynamic mission abort and components allocation policies are developed;•Mission reliability and system survivability are evaluated under the proposed policies;•Joint optimization model is established to find the optimal abort and allocation policies
Mission abort is an effective way to enhance system safety during mission execution. Existing multi-attempt mission abort models can be divided into two main categories according to the additivity of completed missions: non-accumulative models and completely cumulative models. This paper studies the optimal mission abort and allocation of standby components policies for the k-out-of-(n+m):F system considering partial mission loss. During each attempt, the mission abort decision is dynamically controlled via predetermined abort thresholds and the rescue procedure (RP) starts immediately upon mission abort. In most studies, after a successful RP, the system is commonly restored to an ‘as good as new’ state with the underlying assumption that the standby components are always adequate. However, due to factors such as cost and capacity, the number of standby components may be limited. This paper proposes a dynamic allocation policy of a fixed number of standby components. The aim is to determine the optimal number of the failed components be replaced after each RP. By using a recursive algorithm, mission reliability and system survivability are derived. The objective is to minimize the expected cost and balance the mission reliability and the system survivability. The advantage of the proposed policy is justified by the policy comparison. Finally, the obtained results are demonstrated considering an autonomous underwater vehicle performing a photography mission.</description><subject>Algorithms</subject><subject>Allocation of standby components</subject><subject>Autonomous underwater vehicles</subject><subject>Mission abort</subject><subject>Mission reliability</subject><subject>Optimization</subject><subject>Partial replacement</subject><subject>Photography</subject><subject>Reliability engineering</subject><subject>Survivability</subject><subject>System reliability</subject><subject>System survivability</subject><subject>Underwater photography</subject><subject>Underwater vehicles</subject><issn>0951-8320</issn><issn>1879-0836</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kM1KxDAUhYMoOI6-gKuC645JmjYJuJHBXwbc6DqkSSopbVKTjDA-vSmVWbq6l8N37j0cAK4R3CCImtt-E0yMGwwxzgJrED4BK8QoLyGrmlOwgrxGJaswPAcXMfYQQsJrugLtq7cuFX5KdrQ_MlnvCt8Vo41xXmXrQ4qFdLqQw-DVEYgpa-2hUH6cvDMuQ8q7aLUJ1n0e_YOP8RKcdXKI5upvrsHH48P79rncvT29bO93pcI1SyWnhiBNu5abytRKUdPpqiUyC5ooyTuiWCVbAmtIMaOMNohDTmqmEIGtRtUa3Cx3p-C_9iYm0ft9cPmlwA1HDFNIm0zhhVIhZwumE1OwowwHgaCYuxS9mLsUc5di6TKb7haTyfm_rQkiKmucMtoGo5LQ3v5n_wXFjX9H</recordid><startdate>202209</startdate><enddate>202209</enddate><creator>Zhao, Xian</creator><creator>Dai, Ying</creator><creator>Qiu, Qingan</creator><creator>Wu, Yaguang</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>SOI</scope></search><sort><creationdate>202209</creationdate><title>Joint optimization of mission aborts and allocation of standby components considering mission loss</title><author>Zhao, Xian ; Dai, Ying ; Qiu, Qingan ; Wu, Yaguang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c258t-97e41d7fb9e3e5cc7efd3b4afb9d4ca9f4c83ab405072878761909458c140bd13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Allocation of standby components</topic><topic>Autonomous underwater vehicles</topic><topic>Mission abort</topic><topic>Mission reliability</topic><topic>Optimization</topic><topic>Partial replacement</topic><topic>Photography</topic><topic>Reliability engineering</topic><topic>Survivability</topic><topic>System reliability</topic><topic>System survivability</topic><topic>Underwater photography</topic><topic>Underwater vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, Xian</creatorcontrib><creatorcontrib>Dai, Ying</creatorcontrib><creatorcontrib>Qiu, Qingan</creatorcontrib><creatorcontrib>Wu, Yaguang</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Environment Abstracts</collection><jtitle>Reliability engineering & system safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Xian</au><au>Dai, Ying</au><au>Qiu, Qingan</au><au>Wu, Yaguang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Joint optimization of mission aborts and allocation of standby components considering mission loss</atitle><jtitle>Reliability engineering & system safety</jtitle><date>2022-09</date><risdate>2022</risdate><volume>225</volume><spage>108612</spage><pages>108612-</pages><artnum>108612</artnum><issn>0951-8320</issn><eissn>1879-0836</eissn><abstract>•Dynamic mission abort and components allocation policies are developed;•Mission reliability and system survivability are evaluated under the proposed policies;•Joint optimization model is established to find the optimal abort and allocation policies
Mission abort is an effective way to enhance system safety during mission execution. Existing multi-attempt mission abort models can be divided into two main categories according to the additivity of completed missions: non-accumulative models and completely cumulative models. This paper studies the optimal mission abort and allocation of standby components policies for the k-out-of-(n+m):F system considering partial mission loss. During each attempt, the mission abort decision is dynamically controlled via predetermined abort thresholds and the rescue procedure (RP) starts immediately upon mission abort. In most studies, after a successful RP, the system is commonly restored to an ‘as good as new’ state with the underlying assumption that the standby components are always adequate. However, due to factors such as cost and capacity, the number of standby components may be limited. This paper proposes a dynamic allocation policy of a fixed number of standby components. The aim is to determine the optimal number of the failed components be replaced after each RP. By using a recursive algorithm, mission reliability and system survivability are derived. The objective is to minimize the expected cost and balance the mission reliability and the system survivability. The advantage of the proposed policy is justified by the policy comparison. Finally, the obtained results are demonstrated considering an autonomous underwater vehicle performing a photography mission.</abstract><cop>Barking</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ress.2022.108612</doi></addata></record> |
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subjects | Algorithms Allocation of standby components Autonomous underwater vehicles Mission abort Mission reliability Optimization Partial replacement Photography Reliability engineering Survivability System reliability System survivability Underwater photography Underwater vehicles |
title | Joint optimization of mission aborts and allocation of standby components considering mission loss |
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