ArticleScientific reports2025
Experimental investigation of process parameters and mechanical properties in robotic large-scale polymer 3D printing.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Investigating Process-Structure-Property Relationships in Large-Scale Additively Manufactured Carbon-Filled PETg.Materials (Basel, Switzerland) · 2026Article
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Authors and funding
4 authors.
Funding
Abstract
Large-scale additive manufacturing (LSAM) has become a focal point for industries requiring large structures, such as marine, wind, etc. Despite its potential, LSAM faces limitations due to challenges associated with proper slicing software and limited knowledge of the various process parameters and their effect on the mechanical properties of 3D printed specimens. The present study addresses the development of a large-scale robotic 3D printer, followed by a comprehensive experimental investigation of influential printing process parameters. A series of experiments is conducted to explore the influences of different process parameters, such as printing speed, feeding rate, temperature, etc., on the geometrical dimension of the printed rasters and the mechanical properties and structural integrity of the 3D printed specimens. Appropriate printing process parameters for overhanging and bridging specific to LSAM are examined. Furthermore, the influence of the most critical parameters, such as the printing temperature, on the mechanical strength of the 3D-printed specimens is evaluated. LSAM process parameter investigation and mechanical tensile testing on 3D printed specimens offer insight into optimizing LSAM processes, contributing valuable guidelines for advancing robust and efficient large-scale robotic 3D printing.
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Registered trials
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