The combination of computational design techniques and additive manufacturing (AM) shows great promise for producing innovative designs in various industries such as automotive, aerospace, sports equipment, and biomedical engineering. The current high-resolution printing capabilities allow for the creation of intricate shapes like lattice structures, which can be optimized using advanced design tools.

This work introduces an optimization workflow that employs field-driven design to locally adjust lattice structure parameters based on data from topology optimization. This approach automates the nTop design software with Python scripts to enhance mechanical performance by evaluating numerous design variants and systematically identifying the optimal solution. The benefits of this method include improved material usage efficiency, resulting in lighter and more sustainable parts with enhanced structural performance. This is achieved by tailoring the material distribution to the specific needs of the application and creating innovative designs with complex geometries that are challenging or impossible to produce with traditional manufacturing methods.

To effectively demonstrate the practical applicability of the workflow in fields in which weight is a critical factor, it was used to optimize the mechanical performance of a water sports component. The resulting behaviour will be validated by Finite Element Method (FEM) analysis to assess the effectiveness of the presented workflow and its potential for the design and optimization of performance-driven components.

As an application of this work, a prototype of the optimized component will be additively manufactured employing a cork-based polymeric composite material. This approach ensures that both the design process and the specific material employed contribute to the objective of reducing the overall product's environmental impact.