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.

辊磨车间是一种典型的多单元多任务制造方案，其目的是修复由轧制过程引起的辊表面损伤，从而使辊可以重复使用。由于辊磨车间的工艺复杂性以及辊的体积和重量较大，因此需要使用多台起重机进行提升和运输方式。因此，辊磨车间的调度既要考虑任务的时间顺序，又要考虑空间中多起重机轨迹的无干扰性。本文基于复杂任务和时空耦合约束的特点，研究了辊磨车间的智能调度。首先，基于优先级规则和过程约束建立调度基础。为了解决时空耦合约束下的调度问题，建立了位置坐标系，并提出了无干扰的起重机位置跟踪和协调运动算法。此外，考虑到起重机的运输时间及其与过程的不同步时间，基于定义的动态优先级策略开发了智能决策和调度算法，以实现调度，包括时间决策，起重机决策和过程决策。应用开发的智能调度算法，在优先策略和非干扰策略三种组合下对辊磨车间进行仿真，以验证算法的性能。为了保证起重机在整个生产过程中不受干扰，与现有的行业加工方式相比，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）最高可达到100％，以避免调度中两个流程之间的间隔。本文开发的动态优先级显示出比MOR原理更高的效率，而使用策略B，在足够的机器条件下，CUR（起重机利用率）可以提高20％以上，这有助于获得比策略A更短的制造时间。所开发的智能调度算法保证了在复杂约束下多单元多任务调度的有效性和合理性。最后，为了实现辊磨车间的自动化和智能化操作，