制造业的人工智能驱动的数字双胞胎:跨层次层次制造系统层次的综述
Phat Nguyen1, Minjung Kim1, Elaina Nichols1
1Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487, USA.
Sensors (Basel, Switzerland)
|January 10, 2026
概括
通过人工智能 (AI) 增强的数字双胞胎 (DTs) 正在彻底改变智能制造. 由人工智能驱动的DTs能够实现实时优化和自主控制,将行业从机器转变为企业级别.
科学领域:
- 制造业 制造技术 制造技术
- 人工智能的人工智能
- 数字系统 数字系统
背景情况:
- 数字双胞胎 (DTs) 最初是先进的模拟模型.
- 人工智能 (AI) 的整合显著发展了DT的能力.
- 人工智能增强了数据技术,用于获取知识,优化和自主控制.
研究的目的:
- 为制造业中人工智能驱动的数据技术提供最先进的审查.
- 突出关键的应用,挑战和未来的研究方向.
- 在整合层面上对人工智能驱动的数据技术的演变和可扩展性进行结构化.
主要方法:
- 在制造业中对人工智能驱动的DT进行文献调查.
- 分析人工智能技术,如深度强化学习和CNN.
- 根据整合水平对案例研究进行分类:机器,单元,车间和企业.
主要成果:
- 由人工智能驱动的DTs可以实现预测性维护,流程优化,质量控制和动态调度.
- 在数控加工,机器人和工业印刷领域的成功部署显示了效率和可靠性的提高.
- 从单个资产到相互连接的制造生态系统的可扩展性.
结论:
- 人工智能驱动的数据技术正在将制造业转变为智能,适应性系统.
- 高准确度的实时数据和无的物理数字对齐对于智能数据技术至关重要.
- 未来的研究将专注于进一步增强人工智能驱动的数据技术的能力和整合.
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