Inline Monitoring the Degree of Curing in RTM Processes by using of Near-Infrared Spectroscopy

In the realm of modern manufacturing, the quest for lightweight, high-strength components has fueled the adoption of innovative techniques. One such method that has garnered significant attention is Resin Transfer Molding (RTM). This closed-mold process offers a versatile and cost-effective solution for crafting intricate composite structures used in diverse industries, including automotive, aerospace, and marine applications.

Figure 1: Resin transfer molding.

INTRODUCTION

RTM stands out for its ability to produce complex, large-scale parts with exceptional strength-to-weight ratios. The process involves the injection of liquid thermosetting resin into a closed mold cavity, where it undergoes a controlled curing process, resulting in a robust composite material. The advantages of RTM extend beyond its efficiency, encompassing the flexibility to tailor materials for specific performance requirements and the incorporation of reinforcing elements like fiberglass or carbon fiber.

A critical aspect of the RTM process lies in achieving the optimal degree of curing, ensuring the composite components meet stringent standards for strength and durability.

Traditional methods of monitoring the degree of curing in RTM processes often involve post-curing inspections or destructive testing. While these methods provide valuable data, they lack the immediacy and precision required for real-time adjustments during production. This gap in monitoring can lead to variations in product quality and may impact the overall efficiency of the manufacturing process.

Near-infrared spectroscopy (NIR) allows manufacturers to monitor the curing degree inline – directly within the closed mold. This non-destructive analytical technique leverages the interaction between near-infrared light and the chemical bonds within the curing resin. By analyzing the resulting spectra, operators gain real-time insights into the resin's molecular structure, enabling them to assess the degree of curing with unprecedented accuracy.

Key Advantages of NIR in RTM:

• Real-Time Insights: NIR provides continuous, real-time monitoring of the curing process, allowing operators to make immediate adjustments as needed.
• Non-Destructive Nature: Unlike traditional methods, NIR does not require the destruction of samples for analysis. This preserves the integrity of the production process and reduces waste.
• Increased Precision: The high sensitivity of NIR enables manufacturers to detect subtle changes in the chemical composition, ensuring precise control over the degree of curing.
• Process Optimization: Inline monitoring with NIR empowers manufacturers to optimize curing parameters, resulting in consistent and high-quality composite products.

METHODS

An absorbance system is used in this application. The absorbance indicates a small enhancement before the strong reduction during the degree of curing process.

Figure 2: Absorbance spectra at different degrees of curing.

This is obvious because the polymer will contain some functional groups capable of absorbing light to a small extent, which interact with the light and cause the initial absorbance to increase. Until the functional group happens in chemical or physical reactions, these functional groups are no longer able to absorb light, leading to reduced absorption capacity.

The absorption spectrum is produced by Near Infrared Spectroscopy (NIRS), which provides a wealth of chemical information about the curing resin. However, converting this complex spectral data into specific information to predict the curing process requires robust calibration models.

Partial least squares regression is a multivariate statistical method used to model the relationship between two sets of data – in this case, absorption spectra and corresponding treatment levels. PLS regression identifies the latent variables or factors that capture the maximum variance in both data sets, allowing for predictive modeling.

With the data set obtained from the absorption spectra, a Partial Least Squares regression model was used to predict the degree of curing. In general, multivariate PLS, the model for the spectra is written as:

X=T × P^T+E

Where X is the initial spectra, P is the loading matrix, T is called the scores, and E is an error.

With this algorithm, the predicted data is described almost accurately. The error is small, and there is no obvious increase in error over the predicted data points.

APPLICATIONS

The application of inline monitoring of the degree of curing in RTM processes finds utility across various industries where composite materials are employed. Some key industries include:

• Aerospace
• Automotive
• Marine
• Wind Energy
• Sports and Recreation
• Home and Building

Figure 3: Applications for RTM processing.

In the aerospace sector, Inline monitoring of curing degree in RTM processes is used to maintain strict quality control during the production of composite components for aircraft. In the aerospace sector, composite materials are extensively used due to their high strength-to-weight ratio and resistance to corrosion. However, ensuring the quality and integrity of these composite components is crucial for the safety and performance of aircraft.

Another application of inline monitoring of the degree of curing in RTM processes is in the automotive industry, particularly in the production of lightweight composite parts for vehicles. Components such as body panels, interior trim, and structural reinforcements are often made using RTM processes due to their ability to produce complex shapes and achieve high strength-to-weight ratios.

By continuously monitoring the curing process, manufacturers can detect any variations or defects in real time, allowing for immediate adjustments to the production parameters. Consistent monitoring helps prevent issues such as resin under-curing, which can result in reduced mechanical properties and structural integrity of the composite parts. It also enables optimization of the curing cycle parameters, leading to shorter production times and improved efficiency.

recommended EQUIPMENT

INTINS offers the NIRQuest+ spectrometer series with many options for different wavelength ranges from 900 nm to 2450 nm. High sensitivity and good resolution make this model the top welding choice for NIR applications.

Low LOD helps detect weaker light sources and uses shorter integration times to acquire spectra. Good thermal stability cools up to -20^oC for low dark current performance.

Figure 4: NIRQuest+ Spectrometer.