ABSTRACT Real‐time sensing has become increasingly important in injection molding for understanding melt behavior and improving part quality. Cyclo‐olefin copolymer (COC) is widely used in high‐precision optical components and medical devices due to its excellent optical clarity, low birefringence, and dimensional stability, particularly under cold‐climate and low‐temperature operating conditions, where conventional amorphous polymers may suffer from increased residual stress and optical distortion. Ensuring stable processing and reliable performance of COC components in such environments therefore requires enhanced process monitoring and control strategies. In this study, in‐mold pressure sensing combined with birefringence analysis was employed to investigate the relationship between pressure evolution and residual stress in injection‐molded COC components. Two pressure sensors were embedded at the gate and at the cavity center to characterize pressure drop behavior and a pressure‐derived viscosity index under near‐gate and far‐gate configurations. By integrating real‐time pressure data with optical stress analysis, this work demonstrates how smart sensing strategies can be used to ensure product quality, dimensional precision, and optical performance in injection‐molded COC parts. The results show that the cavity pressure drop was approximately 64% lower than the gate pressure in the near‐gate configuration, with a similar but reduced trend observed in the far‐gate configuration. Consistent variations were also identified in the viscosity index. An increased gate‐to‐cavity pressure drop was found to correlate strongly with improved geometric precision, reflected by reduced out‐of‐roundness, and with lower internal residual stress as revealed by birefringence patterns. Increasing mold and melt temperatures improved flow relaxation but introduced trade‐offs in dimensional stability between regions near and far from the gate. These findings demonstrate the coupled effects of pressure evolution and thermal conditions on part quality and highlight the importance of holistic process optimization in precision injection molding.
Shih et al. (Thu,) studied this question.