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Additive Manufacturing of Polypropylene: A Screening Design of Experiment Using Laser-Based Powder Bed Fusion
Department of Materials and Production, Section of Sustainable Production, Faculty of Engineering and Science, Aalborg University, Copenhagen, Denmark.
Department of Mechanical Engineering, School of Engineering, Aalto University, Espoo, Finland.
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-9362-8328
2018 (English)In: Polymers, ISSN 2073-4360, E-ISSN 2073-4360, Vol. 10, article id 1293Article in journal (Refereed) Published
Abstract [en]

The use of commodity polymers such as polypropylene (PP) is key to open new market segments and applications for the additive manufacturing industry. Technologies such as powder-bed fusion (PBF) can process PP powder; however, much is still to learn concerning process parameters for reliable manufacturing. This study focusses in the process–property relationships of PP using laser-based PBF. The research presents an overview of the intrinsic and the extrinsic characteristic of a commercial PP powder as well as fabrication of tensile specimens with varying process parameters to characterize tensile, elongation at break, and porosity properties. The impact of key process parameters, such as power and scanning speed, are systematically modified in a controlled design of experiment. The results were compared to the existing body of knowledge; the outcome is to present a process window and optimal process parameters for industrial use of PP. The computer tomography data revealed a highly porous structure inside specimens ranging between 8.46% and 10.08%, with porosity concentrated in the interlayer planes in the build direction. The results of the design of experiment for this commercial material show a narrow window of 0.122 > Ev > 0.138 J/mm3 led to increased mechanical properties while maintaining geometrical stability.

Place, publisher, year, edition, pages
Springer, 2018. Vol. 10, article id 1293
Keywords [en]
Additive manufacturing; powder-bed fusion; laser sintering; polypropylene; process parameter optimization; mechanical properties; computed tomography
National Category
Engineering and Technology Chemical Process Engineering
Identifiers
URN: urn:nbn:se:oru:diva-70289DOI: 10.3390/polym10121293OAI: oai:DiVA.org:oru-70289DiVA, id: diva2:1265082
Available from: 2018-11-22 Created: 2018-11-22 Last updated: 2018-11-22Bibliographically approved

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2122232425262724 of 130
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