Despite continuous technological enhancements of metal Additive Manufacturing (AM) systems, the lack of process repeatability and stability still represents a barrier for the industrial breakthrough. The most relevant metal AM applications currently involve industrial sectors (e.g. aerospace and bio-medical) where defects avoidance is fundamental. Because of this, there is the need to develop novel in situ monitoring tools able to keep under control the stability of the process on a layer-by-layer basis, and to detect the onset of defects as soon as possible. On the one hand, AM systems must be equipped with in situ sensing devices able to measure relevant quantities during the process, a.k.a. process signatures. On the other hand, in-process data analytics and statistical monitoring techniques are required to detect and localize the defects in an automated way. This paper reviews the literature and the commercial tools for in situ monitoring of powder bed fusion (PBF) processes. It explores the different categories of defects and their main causes, the most relevant process signatures and the in situ sensing approaches proposed so far. Particular attention is devoted to the development of automated defect detection rules and the study of process control strategies, which represent two critical fields for the development of future smart PBF systems.
|Titolo:||Process defects and in situ monitoring methods in metal powder bed fusion: A review|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||01.1 Articolo in Rivista|
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|Process defects and in situ monitoring methods in metal powder bed fusion a review.pdf||PDF editoriale||Accesso riservato|
|Grasso_colosimo_Review_PBF_revised_3.pdf||Post-print||Accesso aperto dal 01/03/2018|