基于数字孪生的高级计划排程优化方法

Optimization Method of Advanced Planning and Scheduling Based on Digital Twin

针对目前计划排程软件难以优化不同设备组合的缺点,提出了基于数字孪生的高级计划排程(APS)优化方法。以某机加工企业三级流水线为研究对象,采用数字孪生平台Emulate3D构建数字孪生模型,计算出生产时间和设备空闲率等性能指标;设计并实施正交试验,构建神经网络模型拟合设备数量组合与性能指标的关系,通过启发式算法NSGA-Ⅱ寻优得到五种产品最优设备数量组合;进一步分析结果表明成型工序是流水线生产瓶颈,今后可优化生产资源配置。提出的数字孪生和优化方法可促进生产降本增效,为排程优化和资源配置提供有益参考。

Aiming at the deficiency of current scheduling software to optimize different equipment combinations,an advanced scheduling and planning(APS)optimization method based on digital twins is proposed.Taking a 3-stage production line of a manufacturing enterprises as the research object,the digital twin model was built by the platform named Emulate3D,and the performance indexes,i.e.productive time and equipment idle rate can be calculated;Then the orthogonal experiments were design and implemented,the neural network model to fit the relationship between the combinations of equipment quantity and performance indexes was established;Finally the optimal equipment quantity combinations of five products by heuristic algorithm NSGA-Ⅱ were obtained.Further analysis shows that the shaping process is the bottleneck of the production line,which can be optimized for resources allocation in the future.The digital twin and optimization method proposed in this paper can promote cost reduction and efficiency increase in manufacturing and as a useful reference for scheduling optimization and resource allocation.