Fusion of NSGA-II and Latin hypercube sampling for optimizing node displacement in thin-film IME molding

In the high-risk environment of firefighting operations, the safety of firefighters depends on the performance of advanced protective equipment. This paper proposes a magnetic levitation shield that combines thin-film in-mold electronic (IME) forming technology and magnetic levitation control as protective equipment. Its non-contact and high strength characteristics ensure the safety of firefighters. However, the execution of the shield's protective function is inseparable from the precise control of the magnetic levitation system, so the defects in the circuits formed by the IME need to be controlled to minimize the loss of current and power as much as possible, thereby improving the stability of the shield. Since the degree of defect in the IME circuit has a greater correlation with the node displacement of the product itself, the main objective of this study is to minimize the node displacement of the product by setting different injection molding parameters. Therefore, this paper innovatively combines the non-dominated sorting genetic algorithm II (NSGA-II) with Latin Hypercube sampling (LHS), and combines Moldex 3D to optimize and obtain different Palatto solutions, and finally selects the eligible combination of process parameters based on the research purpose. Through research and discussion, it was found that the synergistic effect of the two led to an optimization rate of 65.7-89.7% for node displacement. Finally, through the analysis of the impact of different degrees of circuit damage caused by different degrees of node displacement on current loss and power loss, the effectiveness of the method was demonstrated in multiple aspects, providing effective safety guarantee for workers in high-risk environments. The research results not only provide a technical solution and theoretical basis for the design, manufacture and maintenance of magnetic levitation shields for firefighters, but also promote the cross-application of in-mold electronic technology and intelligent optimization algorithms, opening up a new path for improving the safety protection level of firefighters in high-risk environments.