• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2025, Vol. 61 ›› Issue (3): 91-104.doi: 10.3901/JME.2025.03.091

• 特邀专栏:人机联合认知赋能的高端装备设计、制造与运维 • 上一篇    

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运维数据与多模态知识驱动的复杂产品改进设计新模式研究

赵欣1, 任杉2, 张耿1, 张映锋1   

  1. 1. 西北工业大学工业工程与智能制造工信部重点实验室 西安 710072;
    2. 西安邮电大学现代邮政学院 西安 710061
  • 收稿日期:2024-03-04 修回日期:2024-06-18 发布日期:2025-03-12
  • 作者简介:赵欣,女,1984年出生,博士研究生。主要研究方向为产品智能设计与运维、知识图谱与产品生命周期管理。E-mail:zhaoxin_ie@mail.nwpu.edu.cn;任杉,男,1985年出生,博士,副教授,硕士研究生导师。主要研究方向为制造业大数据、产品生命周期管理、产品服务系统。E-mail:renshan@xupt.edu.cn;张耿,男,1991年出生,博士,副教授,硕士研究生导师。主要研究方向为智能制造系统、工业物联驱动的智能生产、制造资源服务运行优化。E-mail:geng.zhang@nwpu.edu.cn;张映锋(通信作者),男,1979年出生,博士,教授,博士研究生导师。主要研究方向为物联制造系统、产品服务系统与绿色制造、制造系统智能化。E-mail:zhangyf@nwpu.edu.cn
  • 基金资助:
    NSFC-广东联合基金(U2001201)和国家自然科学基金(52305554)资助项目。

New Pattern of Operation & Maintenance Data and Multi-modal Knowledge Driven Improvement Design for Complex Products

ZHAO Xin1, REN Shan2, ZHANG Geng1, ZHANG Yingfeng1   

  1. 1. Key Laboratory of Industrial Engineering and Intelligent Manufacturing of Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an 710072;
    2. School of Modern Post, Xi'an University of Posts and Telecommunications, Xi'an 710061
  • Received:2024-03-04 Revised:2024-06-18 Published:2025-03-12

摘要: 在分析当前复杂产品制造企业创新发展面临的挑战以及现有产品改进设计方法局限性与设计模式演进方向的基础上,结合复杂产品各生命周期阶段业务决策过程呈现的数据与知识联合驱动的特征,提出一种运维数据与多模态知识驱动的复杂产品改进设计新模式,设计了相应的体系架构,并讨论了其“配置→监控→评估→关联→反馈→改进”运行逻辑,进而提出该模式下的关键技术体系,包括复杂产品运维过程数据主动感知与生命周期数据增值计算、复杂产品关键功能模块性能退化评估与关键设计参数识别、面向复杂产品改进设计的知识建模与设计方案智能配置等。上述技术的实施,可促进复杂产品设计与运维跨阶段、多业务的协同优化,进而提升产品改进设计方案的有效性和方案配置的智能化。所提模式与技术体系对探索引领高端装备制造业发展的制造服务新模式的研究和应用有重要借鉴价值。

关键词: 运维数据, 多模态知识, 改进设计, 产品生命周期

Abstract: Based on analysis of the challenges facing by complex products (CPs) manufacturing enterprises during innovative development, the limitations of existing product improvement design methods and the evolution directions of current product design paradigms, a new pattern and architecture of operation & maintenance (O&M) data and multi-modal knowledge (MMK) driven improvement design for CPs is proposed and designed. The operation logic of "configuration → monitoring → evaluation → correlation → feedback → improvement" for the proposed pattern is discussed. The related key technologies of the new pattern are put forward and elaborated, which included the O&M data proactive perceiving and lifecycle data value-adding calculation of CPs, the key functional modules performance degradation assessment and key design parameters identification of CPs, and the knowledge modeling and design scheme intelligent configuration for CPs improvement design, etc. By applying these technologies, the cross-stage and multi-business collaborative optimization of design and O&M stages can be facilitated effectively. As a result, the effectiveness of product improvement design schemes and the intelligence of scheme configuration processes are enhanced. The proposed new pattern and key technologies could provide important referential value to the research and application of exploring a new manufacturing service mode that leading the development of high-end equipment manufacturing industry.

Key words: operation and maintenance data, multi-modal knowledge, improving design, product lifecycle

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