3D printing control for surface appearance features

Additive manufacturing has revolutionised the way we manufacture objects by allowing us to create complex shapes and structures easily. However, the quality of 3D-printed objects is not solely determined by their geometrical accuracy and mechanical properties, but also by their surface appearance. Recently, there has been a growing interest in developing advanced 3D printing techniques that allow for precise control of surface appearance features. This has been made possible by the advent of new materials, printing technologies, and sophisticated control algorithms.

In this context, the goal of this thesis is to provide an overview of the surface quality and texture from a visual approach, including its current state-of-theart, challenges, and new potential applications for three of the seven main areas in additive manufacturing: Material Extrusion, Vat Photopolymerization, and Powder Bed Fusion. To do so, we discuss the key surface appearance features that can be controlled in additive manufacturing with a focus on the technical design used to achieve them.

In the first part, we describe the concept of multi-material printing by analyzing the multi-extrusion dynamics that control the process and corroborating our understanding with some contributions on goniochromatic-like surfaces and on the development of algorithms to print fast impressions of paintings.

In the second part, we introduce the vat photopolymerization category and the importance of the design in the surface outcome. We extend the discussion including three subtopics, such as the production of diffraction grating surfaces on planar and non-planar geometries, the analysis of optical anisotropy and isotropy of materials produced with different AM technologies and the concept of layerless printing with its challenges and applications. The third part is instead on the selective laser sintering technology, where we assess the accuracy of the process taking into account multiple parameters and providing optimal setups as final recommendations.