• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2026, Vol. 62 ›› Issue (15): 154-170.doi: 10.3901/JME.260618

• 特邀专栏:大模型时代的智能设计与制造 • 上一篇    

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面向圆锥球头铣刀智能设计的多智能体系统

王洪阳, 刘献礼, 岳彩旭, 范梦超, 毛信辉, 胡子豪, 孙亚逊, 陈扬   

  1. 哈尔滨理工大学先进制造智能化技术教育部重点实验室 哈尔滨 150080
  • 收稿日期:2025-10-11 修回日期:2026-02-11 发布日期:2026-10-13
  • 作者简介:王洪阳,男,1994年出生,博士研究生。主要研究方向为刀具智能设计和刀具数控磨削。E-mail:wanghongyang01@outlook.com;刘献礼(通信作者),男,1961年出生,博士,教授,博士研究生导师。主要研究方向为先进切削刀具与工艺技术,数字化加工与智能制造技术。E-mail:xianli.liu@hrbust.edu.cn
  • 基金资助:
    国家自然科学基金(52575485)和黑龙江省自然科学基金杰出青年(JQ2024E008)资助项目。

The Multi-agent System for the Intelligent Design of Taper Ball Endmill

WANG Hongyang, LIU Xianli, YUE Caixu, FAN Mengchao, MAO Xinhui, HU Zihao, SUN Yaxun, CHEN Yang   

  1. Key Laboratory of Advanced Manufacturing and Intelligent Technology of Ministry of Education, Harbin University of Science and Technology, Harbin 150080
  • Received:2025-10-11 Revised:2026-02-11 Published:2026-10-13

摘要: 随着大模型、增强检索与函数调用等技术的突破,AI正逐步掌握制造业所需的复杂技能与专业知识,为其深度赋能工业场景奠定了基础。因此,提出了基于大模型驱动的刀具设计多智能体系统,借助智能体的优势重构传统刀具设计软件架构并显著提升刀具设计效率。同时,将多智能体系统分为任务规划智能体和工具智能体,实现了对复杂刀具设计任务的分解。以圆锥球头铣刀为例,对刀具设计多智能体系统进行实现。首先,深度融合智能体的技术优势与刀具设计核心要素,构建了圆锥球头铣刀设计多智能体系统的架构;然后,搭建了任务规划智能体,对输入的刀具设计需求进行信息提取和任务规划;接着,建立了最佳刀具材料、最佳刀具涂层决策工具和几何参数优化工具,并将其与大模型融合为工具智能体,从而构建了多智能体系统在刀具设计领域的能力;最后,基于Microsoft C#语言、DeepSeek大模型等技术对多智能体系统进行了实现,并且利用钛合金叶轮精加工圆锥球头铣刀设计案例验证了该智能体的有效性。

关键词: 圆锥球头铣刀, DeepSeek大模型, 多智能体系统, 刀具智能设计

Abstract: With breakthroughs in technologies such as large language models, retrieval-augmented generation, and function calling, AI is progressively mastering the complex skills and expertise required in manufacturing, laying the foundation for its deep integration into industrial scenarios. Accordingly, a multi-agent system for the design of cutting tool, driven by large language models, is proposed. Leveraging the advantages of intelligent agents, it restructures the architecture of traditional tool design software and significantly improves the efficiency of cutting tool design. Meanwhile, the multi-agent system is divided into the task extraction agent and task agents, enabling the decomposition of tool design tasks. Taking the taper ball endmill as an example, the multi-agent system for tool design was implemented. First, the technical strengths of agent are deeply integrated with the core elements of tool design to construct the framework of the multi-agent system for taper ball endmill design. Then, the task extraction agent was established to perform information extraction and task planning based on the input cutting tool design requirements. Subsequently, decision-making tools for optimal tool materials and coatings, as well as the optimization tool for geometry parameters, are established and integrated with large language models to form the task agents, thereby building the capabilities of multi-agent system in the field of tool design. Finally, the multi-agent system is implemented using technologies such as Microsoft C# and the DeepSeek large language model, and its effectiveness is validated through a case study involving the design of a taper ball endmill for the precision machining of titanium alloy impellers.

Key words: taper ball endmill, DeepSeek large model, multi-agent system, intelligent design of cutting tool

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