Automobile assembly line communication coordination system and method based on industrial network

By introducing welding sensing modules and edge computing into the automotive assembly line, real-time scoring of welding quality and network causal analysis were achieved, solving the problems of welding time-series sensitivity and quality backtracking, and improving the accuracy and reliability of the production line.

CN121704360APending Publication Date: 2026-03-20SAGE (WUXI) ELECTRONIC TECH CO LTD
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Patent Information

Application Number
CN202511664276.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-13
Publication Date
2026-03-20

AI Technical Summary

Technical Problem

In automotive assembly lines, welding processes are sensitive to timing determinism. Network jitter can cause weld point misalignment or missed welds. Quality backtracking requires large and fine-grained precision, and the coexistence of equipment from multiple vendors leads to deployment uncertainty.

Method used

The system employs a welding sensing module, a raw waveform upload decision module, a quality feedback management module, and a causal judgment model update module. It uses edge computing to perform real-time quality scoring, network isolation, and causal analysis, and implements automatic parameter fine-tuning and redundancy switching to ensure control determinism and data integrity.

Benefits of technology

It reduces the impact of network jitter on welding, ensures the accuracy and consistency of body assembly, improves the reliability of quality traceability and production stability, and reduces rework rate and fault location time.

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Abstract

The invention discloses an automobile assembly line communication coordination system and method based on an industrial network, and relates to the technical field of communication coordination, and the method comprises the steps: calculating a single welding quality score Q in real time for an edge calculation node located at each welding station, generating a welding event fingerprint, and carrying out annular caching; determining whether to upload the high-resolution data and the original waveform to a rear end based on a threshold value and the calculated joint anomaly score; qoS management is carried out on the control flow and the quality return flow; welding event fingerprints reported by the edge are received, backtracking data are stored, a network-quality joint causal analysis model is executed, and model updating is issued; and according to a causal analysis result and a historical model, implementing automatic welding parameter fine tuning, repair welding triggering, local redundancy switching and rollback strategies. According to the method, the problems that the welding process is extremely sensitive to delay jitter and intermittent welding defects and traceability data missing are caused by high-resolution quality data backtracking in an existing automobile assembly production line industrial network are solved.
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