Constrained Efficient Global Optimization for Pultrusion Process

Composite materials, as the name indicates, are composed of different materials that yield superior performance as compared to individual components. Pultrusion is one of the most cost-effective manufacturing techniques for producing fiber-reinforced composites with constant cross-sectional profiles. This obviously makes it more attractive for both researchers and practitioners to investigate the optimum process parameters. Validated computer simulations cost less as compared to physical experiments, therefore this makes them an efficient tool for numerical optimization. However, the complexity of the numerical models can still be “expensive” and forces us to use them sparingly. These relatively more complex models can be replaced with “surrogates,” which are less complex and are therefore faster to evaluate representative models. In this article, a previously validated thermochemical simulation of the pultrusion process has shortly been presented. Following this, a new constrained optimization methodology based on a well-known surrogate method, i.e., Kriging, is introduced. Next, a validation case is presented to clarify the working principles of the implementation, which also supports the upcoming main optimization test cases. This design problem involves the design of the heating die with one, two, and three heaters together with the pulling speed. The results show that the proposed methodology is very efficient in finding the optimal process and design parameters.