Co-authors​ :

 Nitin GUPTA (AUSTRIA), Arunjunai Raj MAHENDRAN (AUSTRIA), Martin KALTENBRUNNER  

This study explores the practical implementation of dielectric analysis (DEA) for real-time monitoring of the curing process of thermoset prepregs, focusing on phenol-formaldehyde-based resin-impregnated paper, a B-stage resin system. These resin-impregnated papers were subjected to high-temperature and pressure conditions in a hot press, transforming them into composites intended for the furniture industry. Understanding the curing behavior is crucial for composite panel manufacturers in determining an optimal pressing time that balances performance and production cost. While conventional methods like Differential Scanning Calorimetry (DSC) are commonly used to analyze curing behavior, they are limited to lab-scale testing and cannot replicate real-time industrial conditions. In contrast, DEA, a real-time cure monitoring technique, measures dielectric property changes during resin cross-linking reactions, providing essential information on the material's cure state. This proactive monitoring offers immediate detection of deviations in crucial curing parameters such as temperature and viscosity during industrial-scale composite production. By promptly identifying and addressing these deviations, manufacturers can prevent defects and ensure consistent product quality. Polyimide sensors with interdigitated electrodes were employed in this study to measure the curing behavior of resin-impregnated paper. Curing experiments for products with varying thicknesses were conducted directly on the production press under dynamic temperature conditions from room temperature to cure temperature. In these experiments log ion viscosity was calculated with respect to time at frequency of 10 kHz. The findings revealed that the curing process for thin boards was incomplete within the designated time frame as ion viscosity does not reach to a plateau before the cooling program starts, whereas thicker boards show a brief plateau hence exhibiting complete curing with a potential time window of 5-7 minutes for possible curing time reduction. This reduction in curing time may lead to enormous amount of energy as well as cost savings. The results highlight the efficacy of DEA as a valuable method for predicting curing behavior, offering practical applicability in an industrial setting for process control. This technology enables manufacturers to optimize product properties and provides a detailed understanding of the system. Further research on optimizing product properties can be done using this to gain deeper insights into the resin system.