High-volume manufacturing of advanced composite parts: reducing waste and curing time while maintaining high performance

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Historically, the manufacture of advanced composite parts has been characterised by low-volume production, but is increasingly moving towards mass production. This new scenario, where competitiveness is on the rise, requires more agile manufacturing of composite parts, which means shorter processes while maintaining the highest quality standards. At the same time, the industry is currently faced with the enormous challenge of minimising composite waste, while the high cost of raw materials threatens its economic stability if this issue is not properly addressed. An analysis of the relevant literature shows that there is no consensus on the definition of a systematic method of continuous improvement aimed at minimising composite waste in the manufacture of high-volume composite parts. Therefore, this thesis begins with the development and implementation of a systematic approach capable of minimising material waste and scrap rates while increasing process efficiency throughout the production of composite products. The Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology has been used with the synergistic support of Value Stream Map (VSM) and Material Flow Analysis (MFA), both adapted to the specificities of composite manufacturing. After implementation on a real production line, the effectiveness of the proposed process is remarkable, as composite waste has been reduced by 21% in 22 weeks, reaching a waste rate below 25%, which is unprecedented in the industry. This has resulted in a cost saving of 18.5% while increasing the throughput of the process on the line by 15%. Meanwhile, the industry is particularly interested in efficiently predicting the curing progress to reduce curing times. Most existing prediction methods can be accurate with certain thermal histories but usually limited to isothermal or constant heating rates. Furthermore, they are restricted to the applied temperature program, establishing then a particular temperature-time dependency that leads to predefining analytical functions adapted to a particular thermal history. This process of adapting the methods to the target temperature program takes massive time and resources. So, the end-user requires more versatile, agile, and simple prediction methods, while keeping acceptable reliability. Accordingly, the second part of this thesis focuses on investigating, applying, and assessing unexplored kinetic methods to flexibly predict epoxy-based composite curing under arbitrary thermal histories. Two specific isoconversional kinetic-based methods have been proposed to predict the course of the reaction for temperature programs composed of nonlinear evolutions such as that of real resin curing cycles. The validity of the prediction methods used to shorten cure cycles in an industrial environment was demonstrated through a thermo-mechanical test campaign. The results showed the feasibility of kinetic models to reduce the resulting cure time in shortened cycles by 72% while maintaining the high-performance properties of the material. The prediction methods involved not only allow designing cure cycles to maximize the degree of cure in the shortest time, but also to reduce heat flow from the exothermic reaction. However, the kinetic models do not consider the heat transfer and thermal conductivity throughout the composite part. Therefore, the accuracy of the predictions might be compromised for thick laminates. Consequently, the last part of the present thesis focuses on implementing complementary methods that consider heat transfer in their formulation to anticipate detrimental thermal effects such as overheating during the curing of composite materials ​
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