In recent years, the literature has paid considerable attention to digital twin technology for the implementation of Industry 4.0 and intelligent manufacturing. Most of the literature argues that simulation models are a key platform for digital twins and considers discrete-event simulation to be a suitable method to model real dynamic manufacturing systems. However, the discrete-event simulation of complex manufacturing systems is a time-consuming process. Therefore, it is difficult to deal with the large-scale discrete optimisation problems in digital twin shop floors. To bridge this research gap, we propose an improved multi-fidelity simulation-based optimisation method based on multi-fidelity optimisation with ordinal transformation and optimal sampling (MO2TOS) in the current research. The proposed method embeds heuristic algorithms to accelerate the solution space search efficiency in MO2TOS. Moreover, we develop an improved multi-fidelity simulation-based optimisation system by integrating the proposed method with discrete-event simulation tools and apply this system to a digital twin-based aircraft parts production workshop. Based on this digital twin shop floor, we conduct different production planning experiments to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed improved multi-fidelity simulation-based optimisation method is well-applied in solving large-scale problems and outperforms other simulation-based optimisation methods.

The forming-sintering process is the bottleneck of the magnetic material manufacturing system in general, which restricts the overall output of the workshop. It is hard to formulate a production plan due to the complex constraints in such production system. In current research, the production planning control framework integrated with DBR (Drum-Buffer-Rope) concept oriented for forming-sintering process is designed. Moreover, a heuristic method considering the constraints of the magnetic material production process is proposed, which standardize and optimize the preparation process of the forming-sintering production plan. The practical application indicates that the heuristic method greatly reduces the number of WIPs, shortens the order manufacturing cycle, and improves the on-time delivery rate and the utilization rate of the sintering furnace, as compared with the current planning method of the enterprise.