# Cure Kinetics-Driven Compression Molding of CFRP for Fast and Low-Cost Manufacturing

## TL;DR

This paper introduces a new method to optimize the curing process of carbon fiber composites, making manufacturing faster and more energy-efficient.

## Contribution

A novel curing cycle optimization method for CFRP using reaction kinetics and a multidimensional scoring system is proposed.

## Key findings

- The proposed method increased manufacturing efficiency by 247.22%.
- Energy consumption was reduced by 35.7% while maintaining product performance.
- Orthogonal experiments validated the reliability of the optimized curing cycles.

## Abstract

Carbon fiber-reinforced polymer (CFRP) composites are widely used in aerospace due to their excellent strength-to-weight ratio and tailorable properties. However, these properties critically depend on the CFRP curing cycle. The commonly adopted manufacturer-recommended curing cycle (MRCC), designed to accommodate the most conservative conditions, involves prolonged curing times and high energy consumption. To overcome these limitations, this study proposes an efficient and adaptable method to determine the optimal curing cycle. The effects of varying heating rates on resin dynamic and isothermal–exothermic behavior were characterized via reaction kinetics analysis using differential scanning calorimetry (DSC) and rheological measurements. The activation energy of the reaction system was substituted into the modified Sun–Gang model, and the parameters were estimated using a particle swarm optimization algorithm. Based on the curing kinetic behavior of the resin, CFRP compression molding process orthogonal experiments were conducted. A weighted scoring system incorporating strength, energy consumption, and cycle time enabled multidimensional evaluation of optimized solutions. Applying this curing cycle optimization method to a commercial epoxy resin increased efficiency by 247.22% and reduced energy consumption by 35.7% while meeting general product performance requirements. These results confirm the method’s reliability and its significance for improving production efficiency.