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Large-scale robotic 3D printing : Standardized tests to dial in new materials for IRBAM architecture

Large Scale Additive Manufacturing (LSAM) technology has emerged as a transformative force in the manufacturing industry. Using robots and advanced material deposition systems, LSAM facilitates the efficient creation of large-scale components with exceptional precision and reduced production times. Beyond its capacity to manufacture complex structures, this technology drives innovation by fostering the exploration of new materials and designs, opening new frontiers in the aerospace, automotive, and construction sectors. The synergy between robotics and additive manufacturing in LSAM represents a significant advancement toward the future of manufacturing, where customization, efficiency, and sustainability are paramount.  Within the framework of this research, conducted in collaboration with ABB and RISE, a series of tests have been developed to optimize printing parameters when transitioning from one material to another. This study showcases how simple adjustments in the workflow of robotic stations can lead to significant improvements in print quality and increased resource efficiency, paving the way for more precise and sustainable manufacturing.  This research has not only generated valuable insights into the behavior of LSAM under different operating conditions but also provided practical solutions for its continuous improvement. These findings are relevant for the continuous improvement of large-scale additive manufacturing processes and provide important insights for future research in the fields of robotics and advanced manufacturing. Additionally, a systematic methodology has been developed to evaluate and validate results, ensuring the reliability and reproducibility of findings. These achievements solidify the role of LSAM as a fundamental technology in the evolution of the manufacturing industry toward a more efficient and sustainable future.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-24035
Date January 2024
CreatorsNieto Pareja, Pablo
PublisherHögskolan i Skövde, Institutionen för ingenjörsvetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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