Digital twin-driven parameter change propagation path optimization for production line variant design

Current mass individualization requires that production lines for processing products be able to quickly vary to adapt to product changes. The variation and propagation of parameters have a central role in the variation process of a flexible production line, which increases the complexity of the design due to the non-unique propagation path of the variation. Obtaining the optimal variant design scheme has become a major challenge for designers. This paper aims to develop a method to determine optimal paths of change propagation. The digital twin-driven framework of parameter correlation path instantiation is presented. The high-fidelity simulation capability of digital twinning will contribute to the fast variant design of flexible production lines at low cost of trial and error. Then, a parameter variation search algorithm based on multi-fork tree has been proposed. The optimal variation design scheme has been achieved for the optimal propagation path of parameter variation from the perspectives of cost, time and complexity. A prototype verification system of production line design based on digital twin is developed to support the instantiation design of parameter change propagation path. An example of mobile phone welding assembly lines was taken to verify the effectiveness of the method.