Optimization of sequence valve gating (SVG) injection molding based on melt front detection (MFD)

This paper proposes a novel optimization method of valve gate (VG) positions and sequences in sequential valve gating (SVG) injection molding based on melt front detection (MFD). The melt front (MF) that presents the filling patterns is one of the most important in-mold conditions regarding the determination of VG positions for mold design and setting of VG sequences for SVG control. Proper VG positions and sequences prevent weld line defects and reduce injection pressure. Traditional SVG control based on the machine filling-start signal requires exhaustive short-shot tests to search for the optimal VG sequences. It is because it should cover every variation of filling patterns resulting from the coupled relationship of VG positions and VG sequences. The main objective of this study is to develop a systematic optimization method for SVG with minimized dependency on human intervention and intuition. The proposed MFD-SVG control based on MF arrival detection simplifies SVG optimization by decoupling VG positions and VG sequences. VG positions are first optimized with consideration of filling balance, flow hesitation, MF speed fluctuation, and injection pressure. After the VG position optimization, VG sequences are then determined to further reduce MF speed fluctuation and injection pressure. The proposed approach not only dramatically shortens time for VG sequence optimization on the shop floor as compared to the traditional SVG control, but also yields better VG positions and sequences, resulting in more balanced filling patterns than manually determined design. This optimization method can contribute to the automated hot-runner mold design based on digital twin and simulation as well as efficient manufacturing process management.