基于综合评分法的托盘机器人柔性调度算法研究

Research on Flexible Scheduling Algorithm for Pallet-Handling Robots Based on Comprehensive Scoring Method

  • 摘要: 在传统的柔性制造系统(FMS)中,通常采用轨道引导车(RGV)作为物料运输工具。然而,由于RGV仅具备单一的储存工位,导致在机床完成加工任务后,必须先进行下料操作,将托盘转移至其他设备的空闲位置,随后才能进行新物料的搬运并送入机床进行再次加工。这种作业模式导致机床在等待过程中耗费大量时间,进而影响了设备的开动率。为解决这一问题,本研究设计了一种工业机器人配合随行托盘的物料搬运方案,并对柔性调度算法进行了深入研究。通过调度机器人进行物料的快速换料操作,显著减少了机床的等待时间,增强了生产线的灵活性,并有效提升了生产效率。

     

    Abstract: In traditional Flexible Manufacturing Systems (FMS), Rail Guided Vehicles (RGV) are commonly used for material transportation. However, due to RGVs'single storage station limitation, completed machining tasks require a sequential process: first unloading pallets to idle positions of other equipment, then transporting new materials to machine tools for subsequent operations. This workflow causes significant machine idle time during waiting periods, reducing equipment operational rates. To address this, we propose a material handling solution combining industrial robots with pallet-following systems and develop an advanced flexible scheduling algorithm. By scheduling robots for rapid material changeovers, this approach significantly reduces machine waiting time, enhances production line flexibility, and effectively improves manufacturing efficiency.

     

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