一个低成本的物联网架构与射频通信和数据分析,用于实时监控服装制造业的生产力
Cong Duy Vo1,2, Thanh-Truong Nguyen1,2, Duy Anh Dang1,2
1Faculty of Mechanical Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, Dien Hong Ward, Ho Chi Minh City, Vietnam.
iScience
|January 21, 2026
概括
本研究介绍了一种低成本的物联网系统,用于实时监控服装线,并使用机器学习进行生产预测. 该系统能够进行主动管理,提高服装行业的效率和竞争力.
科学领域:
- 工业工程 工业工程 工业工程
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
- 机器学习 机器学习
背景情况:
- 服装线的手动生产率监测会导致错误和缺乏实时可见性.
- 发展中国家面临的挑战是传统的,一天结束的手动监控系统.
- 服装行业需要有效的生产力控制,以确保按时交货和竞争力.
研究的目的:
- 设计和实施低成本的物联网架构,用于实时监控线生产率.
- 利用机器学习来提高决策和生产预测.
- 为了能够在服装制造业中进行主动管理和干预.
主要方法:
- 集成的硬件模块 (站和线路层) 具有射频通信.
- 开发了用于数据采集和本地/基于网络的管理平台的固件.
- 在一个递归预测框架中使用随机森林回归模型来预测产出.
主要成果:
- 物联网系统展示了稳定的射频通信,低延迟和超过98%的传输成功率.
- 随机森林模型实现了高预测准确性 (测试数据R2=0.963),在准确性-效率权衡方面表现优于其他模型.
- 该系统促进了有效的线路平衡和目标调整,证实了它对主动管理的实用性.
结论:
- 拟议的低成本物联网系统为服装线提供可靠的实时生产力监控.
- 机器学习,特别是随机森林,通过提供准确的生产预测来增强决策.
- 综合系统支持主动管理,提高服装行业的运营效率和竞争力.
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