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On the nature of the anisotropy of Maraging steel (1.2709) in additive manufacturing through powder bed laser-based fusion processing
Jönköping University, School of Engineering, JTH, Materials and Manufacturing.ORCID iD: 0000-0002-0101-0062
Jönköping University, School of Engineering, JTH, Materials and Manufacturing.ORCID iD: 0000-0003-2929-7891
Jönköping University, School of Engineering, JTH, Materials and Manufacturing.ORCID iD: 0000-0002-3671-8087
Jönköping University, School of Engineering, JTH, Industrial Product Development, Production and Design, JTH, Product design and development (PDD).ORCID iD: 0000-0001-6278-2499
2021 (English)In: Materials & design, ISSN 0264-1275, E-ISSN 1873-4197, Vol. 204, article id 109608Article in journal (Refereed) Published
Abstract [en]

Additive manufacturing is growing rapidly as a manufacturing method. Additive manufacturing is a rapid solidification process and may, as such, generate new microstructures with an improvement of mechanical properties compared to conventional manufacturing. The repeatability and deeper understanding of properties repeatability for both mechanical and thermophysical properties are not well-established. In the current study, a complete analysis of the nature of the anisotropy is experimentally analysed to provide input for better understanding of the printing process and the resulting properties as reliability and predictability are important factors to build trust in a new manufacturing process.

Place, publisher, year, edition, pages
Elsevier, 2021. Vol. 204, article id 109608
Keywords [en]
Additives, Anisotropy, Maraging steel, Rapid solidification, Reliability analysis, Thermodynamic properties, Conventional manufacturing, Laser-based, Manufacturing IS, Manufacturing methods, Maraging, Mechanical, Powder bed, Property, Rapid solidification process, Thermophysical, 3D printers
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:hj:diva-52076DOI: 10.1016/j.matdes.2021.109608ISI: 000670232100002Scopus ID: 2-s2.0-85102415254Local ID: GOA;;730498OAI: oai:DiVA.org:hj-52076DiVA, id: diva2:1539133
Funder
Knowledge Foundation, 20160327Available from: 2021-03-23 Created: 2021-03-23 Last updated: 2021-07-22Bibliographically approved

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Jarfors, Anders E.W.Matsushita, TaishiSiafakas, DimitriosStolt, Roland

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