ArticlePolymers2022
Large-Scale Robot-Based Polymer and Composite Additive Manufacturing: Failure Modes and Thermal Simulation.
Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Investigating Process-Structure-Property Relationships in Large-Scale Additively Manufactured Carbon-Filled PETg.Materials (Basel, Switzerland) · 2026Article
- Thermal Deformation in Non-Planar Large-Scale Additive Manufacturing of ABS: Experimental and Finite Element Analysis.Materials (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Additive manufacturing (AM) of large-scale polymer and composite parts using robotic arms integrated with extruders has received significant attention in recent years. Despite the contributions of great technical progress and material development towards optimizing this manufacturing method, different failure modes observed in the final printed products have hindered its application in producing large engineering structures used in aerospace and automotive industries. We report failure modes in a variety of printed polymer and composite parts, including fuel tanks and car bumpers. Delamination and warpage observed in these parts originate mostly from thermal gradients and residual stresses accumulated during material deposition and cooling. Because printing large structures requires expensive resources, process simulation to recognize the possible failure modes can significantly lower the manufacturing cost. In this regard, accurate prediction of temperature distribution using thermal simulations is the first step. Finite element analysis (FEA) was used for process simulation of large-scale robotic AM. The important steps of the simulation are presented, and the challenges related to the modeling are recognized and discussed in detail. The numerical results showed reasonable agreement with the temperature data measured by an infrared camera. While in small-scale extrusion AM, the cooling time to the glassy state is less than 1 s, in large-scale AM, the cooling time is around two orders of magnitudes longer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.