In recent years, more manufacturing enterprises are building automated flexible production lines (AFPLs) to satisfy the dynamic and diversified demand. Currently, static planning methods can hardly meet the requirements of the dynamic resource allocation for AFPLs. The technologies of the digital twin can help solve dynamic problems. Therefore, we propose a data-driven cloud simulation architecture for AFPLs in smart factories. First, we design a cloud simulation platform as the architecture foundation. Second, we use the data-driven modelling and simulation method to achieve automated modelling. Third, we implement the system on the cloud using Java, MySQL, and the Anylogic platform, and verify the efficiency of the proposed method by experiments in the real workshop of a 3C (Computer, Communication, Consumer electronics) company. The experimental results show the proposed architecture can support the real-time resource allocation decisions to maximise the throughput in AFPLs. This paper makes contributions by proposing an architecture realising automatic modelling and data-driven simulation first in the cloud simulation environment, and filling the gap of dynamic resource allocation in the research of AFPLs.

近年来，越来越多的制造企业正在建设自动化柔性生产线（AFPL），以满足动态和多样化的需求。目前，静态规划方法很难满足AFPL动态资源分配的要求。数字孪生技术可以帮助解决动态问题。因此，我们为智能工厂中的 AFPL 提出了一种数据驱动的云仿真架构。首先，我们设计了一个云仿真平台作为架构基础。其次，我们使用数据驱动的建模和仿真方法来实现自动化建模。第三，我们使用Java、MySQL和Anylogic平台在云端实现了系统，并在一家3C（计算机、通信、消费电子）公司的真实车间中通过实验验证了所提方法的有效性。实验结果表明，所提出的架构可以支持实时资源分配决策，以最大限度地提高 AFPL 的吞吐量。本文的贡献在于提出了一种首先在云仿真环境中实现自动建模和数据驱动仿真的架构，填补了AFPLs研究中动态资源分配的空白。