A novel heuristic optimisation framework for radial injection configuration for the resin transfer moulding process. (February 2023)

• Record Type: Journal Article
• Authors: Chai, B.X.; Eisenbart, B.; Nikzad, M.; Fox, B.; Blythe, A.; Blanchard, P.; Dahl, J.
• Is Part Of: Composites. Volume 165(2023)
• Publication Date: 2023-02
• Subjects: C. Numerical analysis -- C. Process simulation -- E. Resin transfer moulding (RTM) -- E. Resin flow; Composite materials -- Periodicals; Manufacturing processes -- Periodicals; Composite materials; Manufacturing processes; Periodicals; 620.11805
• DOI: 10.1016/j.compositesa.2022.107352
• Languages: English
• ISSNs: 1359-835X

Abstract

Abstract: The optimisation of the Resin Transfer Moulding (RTM) process, a widely adopted composites manufacturing process, has received heavy research attention lately as the demand for lightweight structural components grows. In this study, a novel multistage heuristic optimisation framework is proposed to optimise the radial injection configuration for the RTM process. The optimisation framework begins with a heuristic to identify the suitable search starting point(s) cost-effectively, followed by an iterative local search to rapidly converge to the nearest optimum in the search neighbourhood. Optimisation case studies involving the manufacture of several composite automotive components are performed to evaluate the optimisation performance of the proposed heuristic framework. The proposed heuristic framework's optimisation efficiency and solution optimality are benchmarked against several established optimisation algorithms from the literature. The results convincingly demonstrate that the proposed heuristic optimisation framework is capable of attaining satisfactory outcomes at a significantly reduced computational cost. Limitations of the proposed framework due to its heuristic nature are also discussed.