主办：陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊：1976年
汽车实用技术

汽车实用技术 ›› 2024, Vol. 49 ›› Issue (15): 154-158.DOI: 10.16638/j.cnki.1671-7988.2024.015.031

• 标准·法规·管理 • 上一篇    

基于图数据库的汽车质量追溯数据存储研究

刘文军 1，陈 晨 2   

  1. 1.苏州工业职业技术学院；2.苏州砺行信息科技有限公司
  • 发布日期:2024-08-12
  • 通讯作者: 刘文军
  • 作者简介:刘文军（1981－），男，博士，副教授，研究方向为并行与分布式算法、工业互联网关键技术，E-mail:liuwj @siit.edu.cn。
  • 基金资助:
    江苏省青蓝工程项目（2023QL006）；江苏省教育厅未来网络科研基金资助（FNSRFP-2021-YB-60）；江苏 省高校自然科学基金项目（21KJB520026）；苏州工业职业技术学院科研团队项目（2021KYTD003）。

Research on Automotive Quality Traceability Data Storage Based on Graph Database

LIU Wenjun1 , CHEN Chen2   

  1. 1.Suzhou Vocational Institute of Industrial Technology; 2.Suzhou Lixing Information Technology Company Limited
  • Published:2024-08-12
  • Contact: LIU Wenjun

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摘要： 汽车产业已经成为当前国民经济中的支柱产业，为了应对汽车零部件生产中的质量问 题，目前产业界在生产过程中广泛引入质量追溯系统。现有的质量追溯系统大多基于关系型 数据库构建，而传统的数据库在处理复杂的关系型数据时存在局限性，无法灵活应对质量追 溯的多层次和复杂需求。因此，提出了一种基于图数据库的汽车质量追溯数据存储方法，选 择图数据库作为数据存储方案，并设计了高度灵活的数据模型，包括汽车、部件、工序等之 间的关联关系，以更好地满足汽车零部件生产质量追溯需求。实验结果表明，相较于传统数 据库系统，基于图数据库的方法在查询性能以及数据插入效率方面均表现出显著优势。

关键词: 质量追溯；汽车产业；图数据库；数据存储

Abstract: The automotive industry has become a pillar industry in the current national economy,and in order to address quality issues in the production of automotive parts, the industry has widely introduced quality traceability systems in the production process. Most existing quality traceability systems are built on relational databases, while traditional databases have limitations in handling complex relational data and cannot flexibly meet the multi-level and complex requirements of quality traceability. Therefore, a storage method for automotive quality traceability data based on graph database is proposed, and graph database is selected as the data acquisition storage scheme, and the highly flexible data model is designed, including the correlation relationships between automobiles, components, processes, etc., to better meet the production quality traceability needs of automotive parts. The experimental results show that compared to traditional database systems, methods based on graph database exhibit significant advantages in query performance and data insertion efficiency.

Key words: Quality traceability; Automotive industry; Graph database; Data storage