Cross-Contamination Quantification in Powders for Additive Manufacturing: A Study on Ti-6Al-4V and Maraging Steel.

PBF Ti-6Al-4V cross-contamination maraging steel

Journal

Materials (Basel, Switzerland)
ISSN: 1996-1944
Titre abrégé: Materials (Basel)
Pays: Switzerland
ID NLM: 101555929

Informations de publication

Date de publication:
24 Jul 2019
Historique:
received: 28 06 2019
revised: 18 07 2019
accepted: 20 07 2019
entrez: 27 7 2019
pubmed: 28 7 2019
medline: 28 7 2019
Statut: epublish

Résumé

Metal additive manufacturing is now taking the lead over traditional manufacturing techniques in applications such as aerospace and biomedicine, which are characterized by low production volumes and high levels of customization. While fulfilling these requirements is the strength of metal additive manufacturing, respecting the tight tolerances typical of the mentioned applications is a harder task to accomplish. Powder bed fusion (PBF) is a class of additive manufacturing in which layers of metal powder are fused on top of each other by a high-energy beam (laser or electron beam) according to a computer-aided design (CAD) model. The quality of raw powders for PBF affects the mechanical properties of additively manufactured parts strongly, and therefore it is crucial to avoid the presence of any source of contamination, particularly cross-contamination. In this study, the identification and quantification of cross-contamination in powders of Ti-6Al-4V and maraging steel was performed using scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) techniques. Experimental results showed an overall good reliability of the developed method, opening the way for applications in machine learning environments.

Identifiants

pubmed: 31344794
pii: ma12152342
doi: 10.3390/ma12152342
pmc: PMC6696047
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Horizon 2020
ID : 723699

Références

Mater Sci Eng C Mater Biol Appl. 2015 Mar;48:263-9
pubmed: 25579922
J Res Natl Inst Stand Technol. 2014 Sep 16;119:460-93
pubmed: 26601040
J Mech Behav Biomed Mater. 2017 Jul;71:1-9
pubmed: 28259023
Materials (Basel). 2017 May 12;10(5):null
pubmed: 28772882

Auteurs

Eleonora Santecchia (E)

Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM-UdR Ancona), Via Brecce Bianche 12, 60131 Ancona, Italy. e.santecchia@univpm.it.
Dipartimento SIMAU, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy. e.santecchia@univpm.it.

Paolo Mengucci (P)

Dipartimento SIMAU, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.

Andrea Gatto (A)

Università di Modena e Reggio Emilia, Dipartimento DIEF, Via Vivarelli 10, 41125 Modena, Italy.

Elena Bassoli (E)

Università di Modena e Reggio Emilia, Dipartimento DIEF, Via Vivarelli 10, 41125 Modena, Italy.

Silvio Defanti (S)

Università di Modena e Reggio Emilia, Dipartimento DIEF, Via Vivarelli 10, 41125 Modena, Italy.

Gianni Barucca (G)

Dipartimento SIMAU, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.

Classifications MeSH