Human-Machine Function Allocation Method for Submersible Fault Detection Tasks

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dc.citation.issue22
dc.citation.volume12
dc.contributor.authorYang C
dc.contributor.authorPang L
dc.contributor.authorWu W
dc.contributor.authorCao X
dc.contributor.editorLu B
dc.contributor.editorPiao M
dc.date.accessioned2025-09-19T03:17:19Z
dc.date.available2025-09-19T03:17:19Z
dc.date.issued2024-11-19
dc.description.abstractThe operation and support (OS) officer is responsible for buoyancy regulation and fault detection of onboard equipment in the civil submersible. The OS officer carries out the above tasks through the human-machine interface (HMI) of a submersible buoyancy regulation and support (SBRS) system. However, the OS officer often faces uneven task frequency produced by fault tasks, which leads to an unbalanced mental workload and individual failures. To address this issue, we proposed a human-machine function allocation method based on level of automation (LOA) taxonomy and submersible task complexity (STC), aimed at improving human-machine cooperation in submersible fault detection tasks. Based on this method, we identified the LOA2 as the optimal human-computer function allocation scheme. In this study, three measurement techniques (subjective scale, work performance, and physiological status) were used to test 15 subjects to validate the effectiveness of the proposed optimal human-machine function allocation scheme. The GAMM test results also indicate that the proposed optimal human-machine function allocation scheme (LOA2) can improve the work performance of the operating system officials under low or high workloads and reduce the subjective workload.
dc.description.confidentialfalse
dc.edition.editionNovember 2024
dc.identifier.citationYang C, Pang L, Wu W, Cao X. (2024). Human-Machine Function Allocation Method for Submersible Fault Detection Tasks. Mathematics. 12. 22.
dc.identifier.doi10.3390/math12223615
dc.identifier.eissn2227-7390
dc.identifier.elements-typejournal-article
dc.identifier.number3615
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/73580
dc.languageEnglish
dc.publisherMDPI (Basel, Switzerland)
dc.publisher.urihttps://www.mdpi.com/2227-7390/12/22/3615
dc.relation.isPartOfMathematics
dc.rights(c) 2024 The Author/s
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjecthuman-machine function allocation method
dc.subjectlevel of automation
dc.subjecttask complexity
dc.subjectworkload
dc.subjectsubmersible
dc.titleHuman-Machine Function Allocation Method for Submersible Fault Detection Tasks
dc.typeJournal article
pubs.elements-id503042
pubs.organisational-groupOther
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