Agentic AI-enabled Semantic Commissioning of a Cognitive Digital Twin for Reconfigurable Manufacturing

2026-09-08

AI Summary

本文针对可重构制造中认知数字孪生的快速定制调试难题，提出了一种基于代理和AI驱动的工作流方法，通过语义和技术路径实现自动化调试。

Abstract

Rapid bespoke commissioning of the Cognitive Digital Twin (CDT) is a major challenge in reconfigurable manufacturing. Traditional digital twin (DT) construction methods primarily focus on geometric reconstruction, often neglecting the deep semantic integration and functional interoperability necessary for autonomous reasoning. This paper proposes an agent-based, AI-driven workflow to automate end-to-end CDT debugging. The system utilises LangGraph as a multi-agent orchestration engine to achieve dual-path synthesis: the semantic path extracts technical specifications from unstructured documents using Retrieval Augmented Generation (RAG), while the functional path autonomously discovers and binds to real-time industrial telemetry data using Model Context Protocol (MCP). Experimental validation in a robotic machining cell demonstrates that the system achieves a mean average accuracy (mAP) of 97.2% in perception and reduces the deployment cycle from several weeks to an average of 2 hours, marking a paradigm shift from manual scripting to autonomous orchestration.

Problem

• Cognitive Digital Twin
• reconfigurable manufacturing
• semantic integration
• functional interoperability
• autonomous reasoning

Innovation

• Agent-based
• AI-driven
• Semantic Integration
• Functional Interoperability
• LangGraph