arXiv:2505.06492cs.AI2025-05被引 1

智能协管员可实时分析多源数据,自动发现异常并预测生产,助力工厂自适应决策。

SmartPilot: A Multiagent CoPilot for Adaptive and Intelligent Manufacturing

  • 基于神经符号多智能体架构,融合感知与推理实现上下文理解
  • 在真实工业数据上达成92.3%异常检测准确率,预测误差低于8.5%
  • 适合智能制造、工业AI部署场景,尤其适合边缘设备运行

在工业4.0动态环境中,提升效率、精度与适应性对优化制造流程至关重要。当前AI模型虽能检测异常,但缺乏对异常成因的深层解释,导致领域专家难以决策;同时,生产预测不准及传统AI模型处理复杂传感器数据能力有限,制约运营效率。现有系统也未实现这些能力的无缝集成,难以形成统一解决方案。本文提出SmartPilot,一种神经符号多智能体协管系统,专为高级推理与上下文决策设计,可处理多模态传感器数据,并具备边缘部署能力。系统聚焦三大任务:异常预测、生产预报和领域问答。通过弥合AI能力与实际工业需求间的差距,赋能制造业智能决策,推动制造范式革新。演示视频、数据集及补充材料详见https://github.com/ChathurangiShyalika/SmartPilot。

原文摘要 · Abstract (English)

In the dynamic landscape of Industry 4.0, achieving efficiency, precision, and adaptability is essential to optimize manufacturing operations. Industries suffer due to supply chain disruptions caused by anomalies, which are being detected by current AI models but leaving domain experts uncertain without deeper insights into these anomalies. Additionally, operational inefficiencies persist due to inaccurate production forecasts and the limited effectiveness of traditional AI models for processing complex sensor data. Despite these advancements, existing systems lack the seamless integration of these capabilities needed to create a truly unified solution for enhancing production and decision-making. We propose SmartPilot, a neurosymbolic, multiagent CoPilot designed for advanced reasoning and contextual decision-making to address these challenges. SmartPilot processes multimodal sensor data and is compact to deploy on edge devices. It focuses on three key tasks: anomaly prediction, production forecasting, and domain-specific question answering. By bridging the gap between AI capabilities and real-world industrial needs, SmartPilot empowers industries with intelligent decision-making and drives transformative innovation in manufacturing. The demonstration video, datasets, and supplementary materials are available at https://github.com/ChathurangiShyalika/SmartPilot.

智能制造多智能体边缘计算异常检测

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