Overall Research Project Description Additive Manufacturing (AM) has evolved to encompass a three-stage process: design, slicing and toolpath planning, and fabrication. This evolution has led to increasingly intricate component designs, pushing the capabilities of AM systems. Slicing software has also advanced, offering more functionalities and modalities to meet these demands. However, this progress introduces a significant challenge: each new feature in the slicing software adds complexity through additional parameters. The proper use of these parameters requires a deep understanding of material science, engineering principles, and the specific AM technology in use. Users must meticulously link a component's functional requirements, such as thermal and mechanical properties, to precise slicing and toolpath planning parameters. The sensitivity of these parameters is such that minor adjustments can significantly impact the quality and performance of the final component. As the complexity of both components and manufacturing capabilities grows, so does the intricacy of slicing software, creating barriers to accessibility, and reducing user efficiency. There is a clear need for a radical shift in the approach to slicing software to maintain its sustainability and effectiveness.

This project introduces a transformative approach to AM slicing and toolpath planning by focusing on automating the selection of optimal process parameters. We are developing a novel framework that uses advanced three-dimensional fields, incorporating scalar, vector, and tensor elements, to guide the generation of slice surfaces and their associated toolpaths. Utilizing level set methods applied to these fields, the framework aims to intuitively bridge the gap between a component’s properties and the capabilities and limitations of AM systems. This approach simplifies the process, making it more accessible to a broader range of users, while simultaneously enhancing productivity and fostering innovation in the AM sector. Our goal is to create a tool that not only reduces the complexity inherent in parameter selection but also harnesses the full potential of AM technology, paving the way for more advanced and precise manufacturing solutions.