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Benchmark Comparison Data Fusion-Driven Support Resource Demand Modeling and Analysis Method

  • Fan Yang
  • , Zhiyu Jia*
  • , Jingjing He
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Maintenance support resource is the material basis of support system, and the adequacy directly affects the integrity of equipment readiness and efficiency. Based on similar theory, this study focuses on the analysis of equipment system support resource. Combining the concept and influence factors of spare part and support equipment demand, the composition of support resource benchmark comparison system (BCS) is summarized. A data model of support resource analysis based on knowledge graph (KG) is constructed based on benchmark comparison data. Comprehensive consideration the rule-based method, benchmark comparison data is used for spare part and support equipment demand analysis, and a data fusion-driven analysis method of spare part and support equipment demand is proposed. The method effectively utilizes the multi-source historical data of support resource and improves the accuracy and efficiency of support analysis.

Original languageEnglish
Title of host publicationProceedings - 2025 16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages371-375
Number of pages5
ISBN (Electronic)9798331535131
DOIs
StatePublished - 2025
Event16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025 - Shanghai, China
Duration: 27 Jul 202530 Jul 2025

Publication series

NameProceedings - 2025 16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025

Conference

Conference16th International Conference on Reliability, Maintainability and Safety, ICRMS 2025
Country/TerritoryChina
CityShanghai
Period27/07/2530/07/25

Keywords

  • benchmark comparison system
  • data fusion
  • knowledge graph
  • maintenance support resource analysis

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