Journal of Shanghai Jiao Tong University ›› 2021, Vol. 55 ›› Issue (5): 544-556.doi: 10.16183/j.cnki.jsjtu.2020.241

Special Issue: 《上海交通大学学报》2021年12期专题汇总专辑 《上海交通大学学报》2021年“自动化技术、计算机技术”专题

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Dynamic Knowledge Graph Modeling Method for Ship Block Manufacturing Process

SONG Dengqiang, ZHOU Bin, SHEN Xingwang, BAO Jinsong, ZHOU Yaqin   

  1. College of Mechanical Engineering, Donghua University, Shanghai 201620, China
  • Received:2020-07-29 Online:2021-05-28 Published:2021-06-01
  • Contact: BAO Jinsong


In the dynamic and discrete ship block manufacturing process, lack of effective process resource organization and transparency in product processing leads to the problem of high cost and low efficiency for managers to acquire knowledge. A method for dynamic generation and updating of knowledge graph based on processing beat data flow is proposed. The definition of the processing beat data information model is defined by analyzing the processing flow and the station data characteristics of the ship blocks. The graph mapping steps, models, and fusion connection algorithms are proposed for static resources and processing beat data to realize the semantic association of station dynamic time series data and knowledge graphs. Based on the relationship between station process and product structure, the generation of workshop-level dynamic knowledge graph is realized. Taking the production process of a ship block as an example, the knowledge graph visualization prototype system is designed, developed, and verified. The results show that the proposed method is beneficial to the organization, acquisition, and reuse of knowledge in the process of ship block manufacturing.

Key words: knowledge graph, time series data, information model, knowledge organization, ship block manufacturing

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