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相关实验视频

Updated: Jan 7, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

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Published on: August 29, 2025

362

下一代事物的人工智能预测性维护预测性维护

Taimia Bitam1, Aya Yahiaoui1, Djallel Eddine Boubiche1

  • 1LEREESI Laboratory, HNS-RE2SD, Batna 05000, Algeria.

Sensors (Basel, Switzerland)
|December 31, 2025
PubMed
概括
此摘要是机器生成的。

工业5.0通过以人为中心的方法增强了工业生态系统. 支持AIoT的预测性维护 (PdM) 对先进的故障检测和系统弹性至关重要.

关键词:
对事物的人工智能工业5.0 工业 5.0 工业 5.0 工业 5.0 工业预测性维护是预测性的维护.智能制造是智能制造的一种方式.

相关实验视频

Last Updated: Jan 7, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

362

科学领域:

  • 工业工程 工业工程 工业工程
  • 计算机科学 计算机科学
  • 人工智能的人工智能

背景情况:

  • 工业5.0优先考虑以人为中心,可持续和有弹性的工业系统.
  • 传统的维护方法与复杂的,数据驱动的环境作斗争.
  • 预测性维护 (PdM) 对工业5.0的适应性运营至关重要.

研究的目的:

  • 在工业5.0的背景下,系统地审查支持AIoT的PdM.
  • 为人工智能模型,IIoT基础设施和AIoT架构提供统一的分类法.
  • 分析人工智能驱动的技术和特定行业的应用.

主要方法:

  • 对启用AIoT的PdM进行系统的文献综述.
  • 为人工智能模型,IIoT和AIoT架构开发统一的分类学.
  • 对人工智能技术,行业实施和新兴范式的分析.

主要成果:

  • AIoT可实现实时感应,学习和决策,用于PdM.
  • 关键的人工智能技术包括故障检测,剩余使用寿命 (RUL) 估计和规范性行动.
  • 像Edge-Cloud,联合学习和数字双胞胎这样的新兴范式增强了自主维护.

结论:

  • 基于AIoT的PdM是工业5.0目标的基础.
  • 未来的研究应该专注于可解释性,数据质量,网络安全和人类-人工智能合作.
  • 本次审查为开发可扩展和可靠的AIoT-PdM系统提供了一个框架.