计算机应用 ›› 2018, Vol. 38 ›› Issue (10): 3017-3024.DOI: 10.11772/j.issn.1001-9081.2018030614

• 应用前沿、交叉与综合 • 上一篇    下一篇

复杂产品协同设计中数据建模与驱动方法

殷学梅1, 周军华2, 朱耀琴1   

  1. 1. 南京理工大学 计算机科学与工程学院, 南京 210094;
    2. 复杂产品智能制造系统技术国家重点实验室(北京电子工程总体研究所), 北京 100854
  • 收稿日期:2018-03-26 修回日期:2018-05-25 出版日期:2018-10-10 发布日期:2018-10-13
  • 通讯作者: 殷学梅
  • 作者简介:殷学梅(1994-),女,江苏宿迁人,硕士研究生,主要研究方向:协同设计、数据建模、本体、机器学习、数据挖掘;周军华(1984-),男,湖北监利人,工程师,博士研究生,主要研究方向:仿真支撑平台、多学科虚拟样机优化;朱耀琴(1977-),女,江苏无锡人,讲师,博士,主要研究方向:虚拟样机、系统仿真、基于仿真的数据决策。
  • 基金资助:
    工信部2016年智能制造综合标准化与新模式项目。

Data modeling and data-driven method in collaborative design of complex products

YIN Xuemei1, ZHOU Junhua2, ZHU Yaoqin1   

  1. 1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China;
    2. State Key Laboratory of Intelligent Manufacturing System Technology(Beijing General Institute of Electronic Engineering), Beijing 100854, China
  • Received:2018-03-26 Revised:2018-05-25 Online:2018-10-10 Published:2018-10-13
  • Supported by:
    This work is partially supported by the Project of Ministry of Industry and Information Technology for Integrated Standardization of Intelligent Manufacturing and New Pattern Projects in 2016.

摘要: 针对在传统基于工作流的协同设计中,不同专业设计人员交流和任务协调困难导致产品设计效率低下的问题,提出复杂产品"一元三层"数据模型和基于数据驱动的复杂产品协同设计技术。首先采用多维多粒度的数据建模和本体描述方法完成了对复杂产品的信息建模,然后采用基于本体的语义检索技术完成协同设计过程任务的数据订阅,最后实现基于数据订阅/发布的复杂产品任务协同技术。实验结果表明,基于数据驱动的复杂产品协同设计技术解决了传统协同设计过程中不同专业设计人员之间交流与任务协调的困难,实现复杂产品协同设计过程的螺旋式上升,从而提高了产品设计效率。

关键词: 复杂产品, 协同设计, 数据驱动, 数据建模, 语义检索, 订阅/发布

Abstract: In the traditional workflow-based collaborative design, the difficulties of communication and task coordination among different professional designers lead to low efficiency of product design. In order to solve this problem, the "A Meta-model with Three Levels" data model of complex product and data-driven collaborative design technology of complex product based on data driven were proposed. Firstly, multi-dimensional and multi-granularity data modeling and ontology description were used to complete the information modeling of complex products. Then the semantic retrieval technology based on ontology was used to complete the data subscription of the collaborative design process task. Finally, a complex product task collaboration technology based on data subscription/publishing was implemented. The experimental results show that the data-driven collaborative design technology solves the difficulties of communication and task coordination among different professional designers in the traditional collaborative design process, and achieves a spiral of rise product collaborative design process, thereby improving the efficiency of complex product design.

Key words: complex product, collaborative design, data-driven, data modeling, semantic retrieval, subscription/distribution

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