Metallization is a common strategy employed to enhance the electrical and thermal conductivity of polymer matrix composite materials. Nevertheless, metallic deposition on polymer-based materials is challenging due to the inherent limitations related to high temperature exposure of the substrate. In this article, a new technique for the manufacturing of composite laminates and the subsequent metallization by cold spraying of metallic powder is presented. The composite manufacturing route is based on the production of thermoplastic-thermoset hybrid substrates and consisted of two main stages: in the first stage the partial impregnation of a reinforcement textile by a thermoplastic film was promoted by hot pressing compaction. Afterwards, the prepared lamina was vacuum bagged with other reinforcing layers and impregnated by the thermoset catalyzed resin by a vacuum infusion process. Finally, the thermoset and thermoplastic layers were co-cured to increase the adhesion of the substrate with the thermoplastic film. The metallization of composite laminate was obtained through the cold spraying technique, depositing powders on the thermoplastic surface layer. The effect of processing parameters on the coating deposition, quality and microstructure was reported and discussed.
In recent years, the concepts of industry 4.0 are widely spreading in many different sectors, from agriculture to home automation, from transportation systems to manufacturing processes. One of the pillars of this concept is related to the use of robotic cells. The focus of the present work is the robotic automated layup of dry fibrous preforms to be employed in liquid composite molding (LCM) processes. In particular, the article describes a software tool developed to simulate the automated placement and layup of fiber fabrics and tissues on complex shape molds by means of a robotic system. The tool has been coded in Matlab language. An end-effector has been appositely designed for the fiber layup and it has been included in the model. The simulation provides as output the path generation and the configuration of the robotic arm and of end effector along the entire layup process. The implemented code has been compared with the commercial software RoboDK.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.