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Composites production: how to automate without sacrificing high performance?

14 September 2021
Article by Jhonny Rodrigues, researcher, and Luís Pina, coordinating researcher, both dedicated to Industry 4.0 at INEGI.


Composite materials consist of a matrix and reinforcement such as polymers and carbon fibers. It is these fibers that give the composites exceptional structural properties, but it is also what makes them difficult to produce, as they are built layer by layer.

Placing the fiber on the surface of the matrix material is now a manual or semi-automatic process. This process involves two steps: first, planning the direction and orientation of fiber placement based on analysis methods for the main stresses of a structure, and second, selecting the formation process. Although manual fiber placement can be adapted to a variety of complex surfaces, this method compromises the mass distribution, cost and production cycle of a component 1, 2, 3.

Given the growing use of composite materials in various sectors, it is imperative to increase speed and enhance the easy repeatability of production. Automation is undoubtedly the answer to optimizing production processes, but the complexities inherent in composite manufacturing are still challenging.

Complexity of processes makes it difficult to implement industry 4.0

The advent of Industry 4.0 has translated into an increase in the complexity of products and production systems, converging different phenomena in the same process, and creating a high level of non-linearity. This requires advanced mathematical techniques to solve problems, and not only more efficient algorithms, but also good simulation and communication equipment 1.

However, it is necessary to know well the materials that will be used, as well as the process parameters that can be controlled throughout the production phases. Dry or impregnated fibers, for example, are a kind of flexible body and their placement process has special requirements, such as cutting, pressing, solidifying and precision. Route planning and laying processes can therefore be complex and changeable. An error can result in a reduction in quality, and compromise the function and structural performance of component 1, 3.

Cyber-physical systems are key technology to automate

Automating composite production without sacrificing quality and performance is therefore a considerable challenge. But what are the possible answers?

The first step is to integrate computer and control systems in the machines, so that they communicate with each other. To do so, it is necessary to develop physical models of the process and simulate scenarios from sensor data - in short, to develop cyber-physical systems (CPS) capable of controlling the process.

The use of networked machines and sensors, however, generates a high volume of data. These data, despite demanding laborious processing, will be the raw material for intelligent systems, capable of providing a more precise response to the different requests that occur during production and simultaneously, saving time and energy. This information must be properly managed, through a big data environment, giving rise to intelligent factories.

Considering the concept of Internet of Things (IoT) and the new Industrial Internet of Things (IIoT), the communication protocol used in cyber-physical systems, communications may not be limited to the factory network. All data, or some of them, must be made available in a cloud, making room for the development of Enterprise Resources Planning (ERP), Manufacturing Execution Systems (MES) methodologies, among others, creating intelligent production systems, accessible anytime, anywhere 1 .

Personalized approach is INEGI's strategy

This path is also followed at INEGI, whose experimental factories have different equipment for the production of composites. Autonomy and efficiency are a priority, and that's why we continuously carry out upgrades to get closer to full autonomy, without sacrificing quality.

An example of this effort is the recent optimization of an in-situ consolidation machine for unidirectional carbon fibers pre-impregnated with polyamide 6.

In this equipment, three machine operating parameters were optimized as a function of the desired heating temperature of the material. For this purpose, the Open Platform Communication Unified Architecture was used, a data exchange standard (IEC 62541) widely used in industrial equipment communication, applying the concept of secure data transfer and, in parallel, a multiplatform interconnection. This allows different devices to exchange information and to create customized processes.

By modeling and simulating the heating process before, during and after the pressing mechanism, it becomes possible to feed an optimization algorithm in order to calculate the ideal working parameters (such as the relative position of the heating in relation to the material and process speed) taking into account the tape temperatures, to avoid overheating and improve the final product.

With the digital simulation, it is possible to foresee different work scenarios and, by learning during the consolidation process, improve the final result, without the need to totally or partially reprogram the process 3.

With this strategy, we are laying the foundations to optimize the production processes of composites, transferring this knowledge to the industry. We pave the way for a more intelligent and autonomous manufacturing, to produce composites for sectors with demanding requirements, in a cost-effective and competitive way.




References

1  Zhang, L., Wang, X., Pei, J., & Zhou, Y. (2020). Review of automated fibre placement and its prospects for advanced composites. Journal of Materials Science, 55(17), 7121-7155.

2  Sacco, C., Radwan, A. B., Anderson, A., Harik, R., & Gregory, E. (2020). Machine learning in composites manufacturing: A case study of Automated Fiber Placement inspection. Composite Structures, 250, 112514.

3 Rodrigues, J., Silva, F., Santos, J., Tavares, J. M. R., & Pina, L. (2019). Automated in situ consolidation process for pre-impregnated carbon fibers: a cyber-physical approach. Materiales Compuestos, 3(3), 80-89. 

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