Resin Transfer Moulding (RTM) is one of the most promising available technology for manufacturing large complex three-dimensional parts from composite materials with high mechanical performance, tight dimensional tolerance and high surface finish. Some of the parameters that affect process and quality of the finished product are flow and cure of the resin. Nowadays, finite element simulation is regularly used to design injection processes and cure. However, purely predictive simulations suffer from issues related to uncertainty and variability in material state and numerous process parameters. Online monitoring of resin flow in tests is a method that can enhance fidelity of numerical simulation models.
The proposed monitoring system combines dielectric sensors with thermocouples to provide information about frontal flow and degree of cure of the resin. Two implementations of flow sensors are proposed; a global linear sensor and a network of local spot sensors. As regards the location of the sensors can either be tool mounded or embedded at tool surface depending on part’s complexity. Integration and packaging techniques for the designing of the sensor and the tooling will be used to increase sensitivity and reduce the inevitable distortion being introduced by the sensors.
This project is part of a Clean Sky research program and consists of three main partners directed by a Topic Manager. The overall concept addresses the development of a stochastic simulation tool that will be implemented on a pilot RTM line, where evaluation and NDT demonstration runs will take place.