Various design changes are inevitably encountered during the development of a production line. Modelling and robustness analysis of heterogeneous networks of production line parameter correlations is fundamental to ensure the successful implementation of design changes. According to the organisational composition of the production line, a parametric correlation model of the production line is established via multilayer network theory. Using this model, we then proceed with constructing a risk propagation model of production line design changes based on the load-capacity model. This model is capable of characterising the dynamic propagation process of design changes by adjusting load and capacity distribution parameters. The effect of various dimensional parameters of the production line on the robustness of the parameter correlation network is analysed by numerical simulation. Deliberate attack strategies based on out-degree, deliberate attack based on primary charge, and random attack strategies are proposed. The results reveal that deliberate attacks based on the out-degree are more likely to lead to paralysing parameter correlation networks. This paper provides novel insights for production line designers and developers in comprehending dynamic design change propagation. Furthermore, it presents new perspectives for robustness predicting and enhancing production line parameter correlation networks. [ABSTRACT FROM AUTHOR]

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