面向数字孪生的船用柴油机装配车间生产调度

Production scheduling in marine diesel assembly workshops for digital twins

在船用柴油机装配过程中,普遍存在动态扰动事件频发、生产状态监控不足等缺陷,导致生产过程偏离调度计划且无法对扰动事件进行快速响应。为解决调度计划偏差和快速响应这两个难题,将数字孪生技术应用于船用柴油机装配车间生产调度过程中,通过物理装配车间与虚拟装配车间的实时交互快速响应扰动事件并减少调度计划偏差。构建了一种基于数字孪生的船用柴油机装配车间生产调度框架,并对装配调度问题进行描述与建模。详细阐述了动态调度流程并提出了一种基于pareto支配规则的多目标离散蚁狮优化算法来优化最大完工时间和装配班组负荷这两个调度目标,保证了调度方案的实时性和准确性。最后,通过在某型号柴油机装配车间部署运行,验证了此种调度模式的有效性。

In the assembly process of marine diesel engines,there are common defects such as frequent occurrence of dynamic disturbance events and insufficient monitoring of production status,resulting in the deviation of the production process from the scheduling plan and the inability to respond to disturbance events quickly.The technology is applied to the production scheduling process of the marine diesel engine assembly workshop,realizing the real-time interaction between the physical assembly workshop and the virtual assembly workshop,which can quickly respond to disturbance events and reduce the deviation of the scheduling plan.A production scheduling framework of marine diesel engine assembly workshop based on digital twin is constructed,and the assembly scheduling problem is described and modeled.The dynamic scheduling process is expounded in detail,and a multi-objective discrete ant lion optimization algorithm based on Pareto rule is proposed,which optimizes the two scheduling objectives of maximum completion time and assembly team load,and ensures the real-time and accuracy of scheduling.Finally,the validity of the scheduling mode is verified by deployment in a certain type of diesel engine assembly workshop.