DEVELOPMENT OF MULTIFUNCTIONAL COMPOSITE SANDWICH PANELS: PROCESS AND OPTIMIZATION

Introduction: The most common processes for the production of multifunctional composite sandwich panels include vacuum-assisted hand lay-up, vacuum infusion, among others. However, these processes are very human-dependent, especially vacuum-assisted hand lay-up. This work aims to develop, optimize, and validate a controlled vacuum infusion manufacturing process for multifunctional composite sandwich panels, enabling scalable, efficient, and high-quality production while improving mechanical performance and process consistency.

Methods: The developed equipment incorporates dual heated plates operating at temperatures up to 200 °C, segmented thermal zones, and a vertical actuation system to ensure uniform pressure during processing. It enables the manufacture of panels measuring up to 1.0 m × 2.0 m × 0.2 m and can be reconfigured into a 2.0 m × 2.0 m working surface through a rotatable upper plate, enhancing operational flexibility. This configuration allows for the single-step production of sandwich panels via vacuum infusion, significantly reducing production time. Curing cycles were optimized using Differential Scanning Calorimetry (DSC) in accordance with ASTM D3418, considering the limitations of the raw materials. Sandwich panels incorporating glass or basalt fibres, an epoxy matrix, and an extruded polystyrene (XPS) core were produced and evaluated. A comprehensive experimental campaign, including DSC, Barcol hardness, density, fibre and void content, flexural performance, and dimensional stability tests, was conducted following relevant international standards.

Results: The results indicate that sandwich panels manufactured with basalt fibres using the vacuum infusion process exhibit superior overall performance. Additionally, vacuum infusion enables faster and more consistent production compared to vacuum-assisted hand lay-up.

Conclusions: The validated infusion strategy and control system demonstrate strong potential for scalable manufacturing, with further work planned to complete performance validation and refine process optimization.