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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-01242022-154831


Tipo di tesi
Tesi di dottorato di ricerca
Autore
ALDERIGHI, THOMAS
URN
etd-01242022-154831
Titolo
Computational Methods for Improving Manufacturing Processes
Settore scientifico disciplinare
INF/01
Corso di studi
INFORMATICA
Relatori
tutor Dott. Cignoni, Paolo
supervisore Dott. Malomo, Luigi
Parole chiave
  • 3d printing
  • computational fabrication
  • computational geometry
  • computer graphics
  • digital fabrication
  • geometric modeling
  • molding
  • silicone molds
Data inizio appello
21/02/2022
Consultabilità
Non consultabile
Data di rilascio
21/02/2025
Riassunto
The last two decades have seen a rapid and wide growth of digital fabrication machinery and technologies. This led to a massive diffusion of such technologies both in the industrial setting and within the hobbyists’ and makers’ communities. While the applications to rapid prototyping and simple download-and-print use cases can be trivial, the design space offered by these numerically controlled technologies (i.e., 3D printing, CNC milling, laser cutting, etc.) is hard to exploit without the support of appropriate computational tools and algorithms.
Within this thesis, we investigate how the potential of common rapid prototyping tools, combined with sound computational methods, can be used to provide novel and alternative fabrication methods and to enhance existing ones, making them available to non-expert users.
In particular, the contributions presented in this thesis are four. The first is a novel technique for the automatic design of flexible molds to cast highly complex shapes. The algorithm is based on an innovative volumetric analysis of the mold volume that defines the layout of the internal cuts needed to open the mold. We show how the method can robustly generate valid molds for shapes with high topological and geometrical complexity for which previous existing methods could not provide any solution. The second contribution is a method for the automatic volumetric decomposition of objects in parts that can be cast using two-piece reusable rigid molds. Automating the design of this kind of molds can directly impact industrial applications, where the use of two-piece, reusable, rigid molds is a de-facto standard, for example, in plastic injection molding machinery. The third contribution is a pipeline for the fabrication of tangible media for the study of complex biological entities and their interactions. The method covers the whole pipeline from molecular surface preparation and editing to actual 3D model fabrication. Moreover, we investigated the use of these tangible models as teaching aid in high school classrooms. Finally, the fourth contribution tackles another important problem related to the fabrication of parts using FDM 3D printing technologies. With this method, we present an automatic optimization algorithm for the decomposition of objects in parts that can be individually 3D printed and then assembled, with the goal of minimizing the visual impact of supports artifacts.
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