Ship welding production line dynamic scheduling method and system based on AI rearrangement algorithm

By using a dynamic scheduling method based on AI rearrangement algorithms, the problems of low scheduling efficiency and weak anti-interference ability in ship welding production lines have been solved. This has enabled efficient and automated production plan adjustment and real-time monitoring, thereby improving the plan fulfillment rate and production optimization capabilities.

CN122414673APending Publication Date: 2026-07-17CHINA SHIPBUILDING (TIANJIN) SHIPBUILDING CO LTD +1
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Patent Information

Application Number
CN202610543649.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-23
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing ship welding production lines suffer from low scheduling efficiency, reliance on manual experience, incomplete consideration of constraints, delayed response to anomalies, weak anti-interference capabilities, and a lack of real-time monitoring and analysis tools, making it difficult to form a closed loop for production optimization.

Method used

A dynamic scheduling method based on AI rearrangement algorithm is adopted. By establishing a three-level model of order-production line-workstation, it integrates multi-dimensional production constraints such as equipment availability and tooling life, and combines historical cycle data to achieve minute-level executable rolling scheduling. In abnormal scenarios, the AI ​​rearrangement algorithm is triggered to quickly adjust the plan, and it is accompanied by delivery risk warning and bottleneck analysis.

Benefits of technology

It enables automated production planning under multiple constraints and abnormal scenarios, ensuring a plan fulfillment rate of ≥95%, improving scheduling efficiency, reducing capacity waste, and providing real-time decision support and delivery risk warning.

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Abstract

本发明提供了基于AI重排算法的船舶焊接产线动态排程方法及系统,包括:建立产线排程模型,通过产线排程模型生成任务包;根据约束因子筛选任务包,利用筛选后的任务包生成原始排程计划;对原始排程计划进行监测,当原始排程计划触发任意一个故障条件时,采用AI排程算法对原始排程计划重新调整,得到最终排程计划;实时监控最终排程计划,生成KPI指标、全流程数据、负荷率,并对最终排程计划进行交期风险预警。本发明能够对船舶焊接产线的生产计划进行自动排程。
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