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The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop

机译:复杂约束智能调度算法研究和多加工辊磨车间的研究

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Roller grinding workshop is a typical multi-unit and multi-task manufacturing scenario, which is aimed to repair the surface damage of the rollers caused by the rolling process, so that the rollers can be reused. Due to the process complexity of roller grinding workshop and the large volume and weight of the roller, hoisting and transportation mode with multiple cranes is required. Consequently, the scheduling of the roller grinding workshop needs to consider both the task sequencing in time and the noninterference of the multi-crane trajectory in space. In this paper, the intelligent scheduling of roller grinding workshop is studied based on the characteristics of complex tasks and space-time coupling constraints. Firstly, the scheduling basis is established based on priority rules and process constraints. In order to solve the scheduling problem under the space-time coupling constraints, the position coordinate system is established, and then the algorithms of crane position tracking and cooperative motion without interference are developed. Further, considering the transportation time of crane and its out of sync time point with the processes, the intelligent decision and scheduling algorithm are developed based on the dynamic priority strategy defined to realize scheduling, including time decision, crane decision, and process decision. With the developed intelligent scheduling algorithm applied, the simulation of the roller grinding workshop is conducted under three combinations of priority strategy and noninterference strategy to verify algorithm performance. Under the guarantee of crane noninterference during the full production, the efficiency is improved by 22.1% compared with the existing processing mode of industry. Additionally, EPTR (effective process time rate) based on dynamic priority strategy and noninterference strategy B is up to 100% to avoid intervals between two processes in the scheduling. The dynamic priority developed in this paper reveals more efficiency than MOR principle, while with the strategy B the CUR (crane utilization rate) can be improved more than 20% under the condition of enough machines which facilitates to obtain shorter makespan than strategy A. The intelligent scheduling algorithm developed guarantees the effectiveness and rationality of scheduling with multi-unit and multi-task under the complex constraints. Finally, in order to realize the automatic and intelligent operation of the roller grinding workshop, the management software of the roller grinding workshop is developed by integrating the intelligent scheduling algorithm, which realizes the intelligent production, monitoring, and management of the roller grinding workshop during the full production cycle.
机译:滚筒研磨车间是一种典型的多单元和多任务制造场景,旨在修复由轧制过程引起的滚轮的表面损坏,从而可以重复使用辊子。由于辊式研磨车间的过程复杂性以及辊的大容量和重量,需要具有多个起重机的吊装和运输模式。因此,辊子研磨车间的调度需要考虑及时的任务排序和空间中多起重机轨迹的非干扰。本文研究了基于复杂任务和时空耦合约束的特性研究了辊磨车间的智能调度。首先,计划基于优先级规则和过程约束来建立调度。为了在空时耦合约束下解决调度问题,建立位置坐标系,然后开发起重机位置跟踪和合作运动而没有干扰的协作运动。此外,考虑到起重机的运输时间及其与过程的同步时间点,基于定义的动态优先级策略开发了智能判定和调度算法,该策略为实现调度,包括时间决策,起重机决策和过程决策。利用所开发的智能调度算法应用,滚筒研磨车间的仿真在优先级策略和非干扰策略的三种组合下进行,以验证算法性能。根据在全生产中起重机非干扰的保证,与现有的工业加工方式相比,效率提高了22.1%。此外,基于动态优先级策略和非干扰策略B的EPTR(有效处理时间率)高达100%,以避免在调度中的两个过程之间的间隔。本文开发的动态优先级揭示了比Mor原理更高的效率,而在策略B的情况下,在足够的机器的情况下,Cur(起重机利用率)可以提高超过20%,这有助于获得比策略A的更短的Mapshan。该智能调度算法在复杂的约束下,保证了在多单元和多任务下调度的有效性和合理性。最后,为了实现辊式研磨车间的自动和智能操作,通过集成智能调度算法来开发辊磨车间的管理软件,这实现了轧辊研磨车间的智能制作,监控和管理完整的生产周期。

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