制造业的人工智能可靠性:挑战,工具包和通往工业5.0的道路
M Nadeem Ahangar1, Z A Farhat1, Aparajithan Sivanathan1
1AMRC North West, University of Sheffield, Blackburn BB2 7HP, UK.
Sensors (Basel, Switzerland)
|July 30, 2025
概括
在制造业中采用人工智能 (AI) 是工业5.0的关键,但像偏见和缺乏透明度这样的可信度挑战阻碍了进步. 本文调查了制造业中的AI可信度,为道德和可靠的AI系统提供了解决方案.
科学领域:
- 制造业 制造技术 制造技术
- 人工智能的人工智能
- 工业系统工程 工业系统工程
背景情况:
- 工业4.0正在向工业5.0发展,强调以人为中心,可持续和弹性制造.
- 人工智能 (AI) 在这种转型中起着关键作用,使预测性维护,质量控制和供应链优化的进步成为可能.
- 广泛采用人工智能面临重大障碍,包括"黑子"问题,数据偏见,道德考虑以及缺乏强大的可信度框架.
研究的目的:
- 为制造业提供人工智能 (AI) 可信度的全面调查.
- 检查工业范式的演变,并确定人工智能采用的关键障碍.
- 探索人工智能可信度的原则,包括透明度,公平性,稳定性和问责制.
主要方法:
- 关于人工智能在制造业中的可信度的文献评论.
- 对现有的工具包和方法论进行分析,以确定人工智能可解释性,偏差缓解和稳定性.
- 检查人工智能管道中的挑战,从数据收集到模型部署.
主要成果:
- 确定了制造业采用人工智能的关键障碍,包括模型不透明性和数据完整性问题.
- 总结了提高人工智能透明度,公平性和稳健性的现有方法.
- 强调了人工智能生命周期中的挑战,从数据采集到部署.
结论:
- 促进对人工智能系统的信任对于实现工业5.0的全部潜力至关重要.
- 提供了可操作的见解和研究问题,以指导制造业中道德和可靠的人工智能的发展.
- 该研究旨在支持研究人员,从业者和决策者将人工智能进步与社会价值观相协调.
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