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The Adoption of Additive Manufacturing Technology in Sweden
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)
Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering. (Product Development Research Lab)ORCID iD: 0000-0002-9662-4576
2015 (English)In: 3D Printing and Additive Manufacturing, ISSN 2329-7662, Vol. 2, no 4, p. 152-158Article in journal (Refereed) Published
Abstract [en]

This article analyzes the adoption of additive manufacturing (AM) technologies in Sweden. The data set consists of a recent and representative sample of Swedish AM users (companies, universities, and research institutes). The authors investigate two questions. First, what are the current applications of AM in Sweden (e.g., rapid prototyping [RP], production)? Second, what are the factors that can explain the variation in AM adoption among the users? Using a regression analysis technique, the main findings are as follows. (i) There is a variation among users' choice of AM application, and the majority of users are expanding their AM applications beyond RP. (ii) There are two factors that positively affect the decision of firms to expand classical RP and incorporate production and management as well. These two factors are using multiple AM technologies (as opposed to single fused deposition modeling technology) being small companies. The authors discuss the implication of these results.

Place, publisher, year, edition, pages
Mary Ann Liebert, 2015. Vol. 2, no 4, p. 152-158
Keywords [en]
3D printing, additive manufacturing, adoption
National Category
Manufacturing, Surface and Joining Technology Production Engineering, Human Work Science and Ergonomics Other Mechanical Engineering
Identifiers
URN: urn:nbn:se:bth-11342DOI: 10.1089/3dp.2015.0013OAI: oai:DiVA.org:bth-11342DiVA, id: diva2:890293
Part of project
Model Driven Development and Decision Support – MD3S, Knowledge Foundation
Funder
Knowledge FoundationAvailable from: 2016-01-02 Created: 2016-01-02 Last updated: 2021-01-07Bibliographically approved

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Publisher's full texthttp://online.liebertpub.com/doi/abs/10.1089/3dp.2015.0013

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Kianian, BabakTavassoli, SamLarsson, Tobias

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