纺织学报 ›› 2023, Vol. 44 ›› Issue (08): 205-216.doi: 10.13475/j.fzxb.20220305802

• 综合述评 • 上一篇    下一篇

纺织工业智能发展现状与展望

郑小虎1,2(), 刘正好3, 陈峰4, 张洁1,2, 汪俊亮1,2   

  1. 1.东华大学 人工智能研究院, 上海 201620
    2.上海工业大数据与智能系统工程技术研究中心, 上海 201620
    3.东华大学 机械工程学院, 上海 201620
    4.经纬纺织机械股份有限公司, 北京 100176
  • 收稿日期:2022-03-17 修回日期:2022-11-01 出版日期:2023-08-15 发布日期:2023-09-21
  • 作者简介:郑小虎(1983—),男,副教授,博士。主要研究方向为机器人制造技术。E-mail:xhzheng@dhu.edu.cn。
  • 基金资助:
    上海市晨光计划资助项目(20CG41);中央高校基本科研业务费专项资金资助项目(2232021D-15);上海市科技计划项目(20DZ2251400);国家工信部项目(2021-0173-2-1)

Current status and prospect of intelligent development in textile industry

ZHENG Xiaohu1,2(), LIU Zhenghao3, CHEN Feng4, ZHANG Jie1,2, WANG Junliang1,2   

  1. 1. Institute of Artificial Intelligence,Donghua University, Shanghai 201620, China
    2. Shanghai Industrial Big Data and Intelligent Systems Engineering Technology Center, Shanghai 201620, China
    3. College of Mechanical Engineering,Donghua University, Shanghai 201620, China
    4. Jingwei Textile Machinery Co., Ltd., Beijing 100176, China
  • Received:2022-03-17 Revised:2022-11-01 Published:2023-08-15 Online:2023-09-21

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摘要：

为全面了解人工智能技术在纺织工业的发展及应用情况,探究未来智能化发展的任务与目标,基于国内外纺织工业在数字化、网络化、智能化领域的最新发展现状,结合纺织行业的相关需求,分析了当前面临的技术挑战,总结了工业大数据、数字孪生、工业机器人、机器视觉和智能排产调度等当前纺织行业亟需的关键技术;介绍了全流程智能纺织生产线、纺织装备智能运维、纺织品智能检测等典型应用案例和生产模式。最后,总结了我国纺织工业智能化发展进程中仍待突破的核心技术及产业生态的发展方向,提出了发展新一代纺织智能制造系统,打造全产业链协同的纺织智能生态的两点思考与展望,为我国纺织工业智能化发展提供案例参考与技术指引。

关键词: 纺织工业, 纺织智能化, 纺织智能工厂, 智能制造, 工业互联网

Abstract:

Significance With the start of a new round of technological revolution and industrial advancement, China's textile industry has stepped into a new stage of high-quality development. This paper provides a comprehensive overview of the development and application of artificial intelligence technology in the textile industry and explores the tasks and goals of future intelligent development. Based on the latest global developments in digitalization, networking, and intelligence in the textile industry, it analysed the current technical challenges and summarised the key technologies urgently needed in the textile industry. Typical application cases and production models were introduced such as whole-process intelligent textile production lines, intelligent operation and maintenance of textile equipment, and intelligent textile testing. The core technological challenges facing the Chinese textile industry and the development directions of the industrial ecology were to be reviewed. Ideas on developing a new generation of textile-intelligent manufacturing systems and creating an intelligent textile ecology with the collaboration of the whole industrial chain were presented.

Progress At this stage, the Chinese textile industry intelligent manufacturing is in a critical period of digital, networked, and intelligent development (Fig. 1). The critical technologies related to the intelligence of the textile industry are developing rapidly, and big-data technology for the whole textile production process is being applied rapidly (Fig. 2). Digital-twin technology in the textile industry is applied to intelligent garment design and intelligent textile factories (Fig. 3 and Fig. 4). As automated equipment replaces manual labor in typical textile processes, robots in the textile industry have become an essential part of intelligent production. Machine vision technology based on deep learning plays a role in the intelligent control of textile equipment and intelligent inspection of textile quality scenarios (Fig. 5). Intelligent scheduling technology based on machine learning effectively improves the production efficiency of textile enterprises. Based on these technologies, typical examples of intelligent applications in the textile industry have emerged. A data-driven intelligent operation and maintenance system for high-speed winders (Fig. 6), enables data-based intelligent fault diagnosis and remaining life prediction of equipment. The "edge-cloud" collaborative fabric defect detection system enables the detection and identification of a wide range of fabric defects. Xinfengming Group realizes the intelligence of the whole production chain based on 5G and product identification resolution technology (Fig. 7). Wuhan Yudahua's 100000-spindle full-process intelligent spinning line solves the discontinuity problem between some of the ring spinning processes, with an automation rate of over 95% (Fig. 8).

Conclusion and Prospect China's textile industry has made a breakthrough in digitalizing equipment, networking, and workshop intelligence. Significant progress has been made in improving quality and efficiency and optimizing the industrial structure. However, a series of standards system for intelligent manufacturing in the textile industry has yet to be established. In the field of cotton spinning, for example, there are still breakpoints in the automated production of the whole process. The quality traceability of the whole process of product production needs to be strengthened. Data processing and other software are primarily selected from general software developed by information technology developers, which is challenging to meet the precise professional needs of spinning enterprises. The core equipment and industrial software in the field of textiles have not yet formed the technical support capacity, from the true meaning of "intelligent" still has a large gap. The intelligent textile ecology of the whole industrial chain needs to be established. Developing a new generation of intelligent textile manufacturing systems should be based on the study of intelligent textile process, intelligent textile equipment as the focus of development, and intelligent equipment collaboration as the core. At the same time, through the construction of a textile innovative factory demonstration production model, the development of critical technologies of the textile industry Internet, the construction of a blockchain-based networked collaborative rapid response service system, the creation of the whole industry chain collaborative textile intelligent ecology, improve the rapid response service capacity, to achieve the development of the textile industry multi-cluster synergy.

Key words: textile industry, textile intelligence, textile intelligent factory, smart manufacturing, industrial intern

中图分类号: 

  • TP18

图1

纺织工业智能化发展现状"

图2

纺织大数据应用模式"

图3

基于数字孪生的服装设计技术"

图4

基于数字孪生技术的纺纱智能工厂参考模型"

图5

机器视觉技术在纺织领域的应用"

图6

基于机器视觉的面料疵点检测系统"

图7

新凤鸣集团5G智能化生产方案"

图8

裕大华集团智能纺纱管理系统"

图9

纺织工业智能化发展展望"

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