The present paper addresses the multi-objective optimization of the filling stage of the Resin Infusion manufacturing process. The optimization focuses on the selection of an optimal temperature profile which addresses the tradeoff between filling time and the risk of impeding the flow of resin due to excessive curing. The methodology developed combines a numerical solution of the coupled Darcy’s flow and heat conduction problem with a Genetic Algorithm (GA). The methodology converges successfully to a final Pareto set for the case of a C-stiffener which is 130 mm high, 60 mm wide and lies on a skin 280 mm wide. The results highlight the efficiency opportunities available compared to standard industrial manufacturing practice. Reductions in filling time up to 66% and up to 15% in final degree of cure are achieved compared to standard solutions.@en

The impetus for higher performance, robustness and efficiency in the aerospace, automotive and energy industries has been reflected in more stringent requirements which the composite manufacturing industry needs to comply with. The process design challenges associated with this are significant and can be only partially met by integration of simulation in the design loop. The implementation of numerical optimisation tools is therefore necessary. The development of methodologies linking predictive simulation tools with numerical optimisation techniques is pivotal to identify and therefore develop optimal design conditions that allow full exploitation of the efficiency opportunities in composite manufacturing. Numerical and experimental results concerning the optimisation techniques and methodologies implemented in literature to address the optimisation of thermoset composite manufacturing processes are presented and analysed in this study.

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This work reports the development of a methodology for the measurement of thermal conductivity of thermosetting polymers during their cure. The study addresses the reliability and robustness of the method through FEA modeling and testing using a noncuring material with known thermal conductivity. The thermal conductivity and its evolution during the cure has been measured for three widely used aerospace epoxy resins, namely, RTM6, 890RTM, and the XU3508/XB3473 system as function of cure temperature. A constitutive model expressing the dependence of thermal conductivity on the degree of cure and temperature has been established. The device developed here can measure thermal conductivity of epoxy resin with accuracy up to 3%.@en

A stochastic multi-objective cure optimisation methodology is developed in this work and applied to the case of thick epoxy/carbon fibre laminates. The methodology takes into account the uncertainty in process parameters and boundary conditions and minimises the mean values and standard deviations of cure time and temperature overshoot. Kriging is utilised to construct a surrogate model of the cure substituting Finite Element (FE) simulation for computational efficiency reasons. The surrogate model is coupled with Monte Carlo and integrated into a stochastic multi-objective optimisation framework based on Genetic Algorithms. The results show a significant reduction of about 40% in temperature overshoot and cure time compared to standard cure profiles. This reduction is accompanied by a reduction in variability by about 20% for both objectives. This highlights the opportunity of replacing conventional cure schedules with optimised profiles achieving significant improvement in both process efficiency and robustness.

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This paper addresses the multi-objective optimisation of the cure stage of composites manufacture. The optimisation aims to minimise the cure process duration and maximum temperature overshoot within the curing part by selecting an appropriate thermal profile. The methodology developed combines a finite element solution of the heat transfer problem with a Genetic Algorithm. The optimisation algorithm approximates successfully and consistently the Pareto optimal front of the multi-objective problem in a variety of characteristic geometries of varying thickness. The results highlight the efficiency opportunities available in comparison with standard industrial cure profiles. In the case of ultra-thick components improvements of up to 70% in terms of overshoot and 14 h in terms of process time, compared to conventional cure profiles for ultra-thick components, can be achieved. In the case of thick components reduction up to 50% can be achieved in both temperature overshoot and process duration.@en