Salvato in:
Dettagli Bibliografici
Autori principali: Hatton, Hayley, Khalid, Muhammed, Manzoor, Umar, Murray, John
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:https://arxiv.org/abs/2603.29579
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866918419684655104
author Hatton, Hayley
Khalid, Muhammed
Manzoor, Umar
Murray, John
author_facet Hatton, Hayley
Khalid, Muhammed
Manzoor, Umar
Murray, John
contents Much contemporary research in additive manufacturing focuses on breaking down models into constituent parts in the pursuit of various factors, such as printability of large models in smaller printing volumes, or reduction of support structures. Newer research has begun to focus on using these decomposition processes for printing models across multiple printers in parallel. We present a novel approach to this that incorporates axisaligned bounding boxes as height fields to improve the characteristics of decomposition, including printing time, feasibility, and aesthetics. By expanding these bounding boxes according to a parallel printing objective, with additional improved efficiency from a metaheuristic process, these boxes can then be used for rapid decomposition using simple out-of-the-box mesh clipping operations. This algorithm is experimentally evaluated across a range of models against two other contemporary approaches to parallel printing that use more rudimentary techniques, such as recursive symmetry and cube skeletonization. Parallelobox outperformed each of these across a range of sample models on the basis of a parallel printing time metric using simulated 3D printing to compute the results
format Preprint
id arxiv_https___arxiv_org_abs_2603_29579
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Parallelobox: Improved Decomposition for Optimized Parallel Printing using Axis-Aligned Bounding Boxes
Hatton, Hayley
Khalid, Muhammed
Manzoor, Umar
Murray, John
Graphics
Much contemporary research in additive manufacturing focuses on breaking down models into constituent parts in the pursuit of various factors, such as printability of large models in smaller printing volumes, or reduction of support structures. Newer research has begun to focus on using these decomposition processes for printing models across multiple printers in parallel. We present a novel approach to this that incorporates axisaligned bounding boxes as height fields to improve the characteristics of decomposition, including printing time, feasibility, and aesthetics. By expanding these bounding boxes according to a parallel printing objective, with additional improved efficiency from a metaheuristic process, these boxes can then be used for rapid decomposition using simple out-of-the-box mesh clipping operations. This algorithm is experimentally evaluated across a range of models against two other contemporary approaches to parallel printing that use more rudimentary techniques, such as recursive symmetry and cube skeletonization. Parallelobox outperformed each of these across a range of sample models on the basis of a parallel printing time metric using simulated 3D printing to compute the results
title Parallelobox: Improved Decomposition for Optimized Parallel Printing using Axis-Aligned Bounding Boxes
topic Graphics
url https://arxiv.org/abs/2603.29579