Low Coherence Interferometry in Selective Laser Melting

Neef, Arne; Seyda, Vanessa; Herzog, Dirk; Emmelmann, Claus; Schönleber, Martin; Kogel‐Hollacher, Markus

doi:10.1016/j.phpro.2014.08.100

Cited by 72 publications

(32 citation statements)

References 1 publication

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“…A different co-axial sensing technique was proposed by Kanko et al (2016) and Neef et al (2014). It consists of a low-coherence interferometric technique, also termed inline coherent imaging (ICI), suitable for co-axial monitoring of the SLM process at high frequency.…”

Section: Co-axial Sensingmentioning

confidence: 99%

“…A typical ICI system consists of low-power broadband light source (e.g., a super-luminescent diode (SLD)), a high-speed spectrometer and a fiber-based Michelson interferometer (Kanko et al, 2016). Neef et al (2014) first proposed this approach for powder bed uniformity analysis and monitoring of the surface slice patterns. The proposed set-up is based on the PRECITED IDM sensor, with a maximum scan rate of 70 kHz.…”

Section: Co-axial Sensingmentioning

confidence: 99%

“…The proposed set-up is based on the PRECITED IDM sensor, with a maximum scan rate of 70 kHz. Neef et al (2014) discussed different possible applications and showed an example of surface topology reconstruction for both loose powder and molten material. Kanko et al (2016) extended the same technique to the monitoring of the melt pool morphology, with a frame rate of 200 kHz.…”

Section: Co-axial Sensingmentioning

confidence: 99%

See 2 more Smart Citations

Process defects andin situmonitoring methods in metal powder bed fusion: a review

Grasso

Colosimo

2017

Meas. Sci. Technol.

587

246

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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 insitu 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.

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Section: Co-axial Sensingmentioning

confidence: 99%

Section: Co-axial Sensingmentioning

confidence: 99%

Section: Co-axial Sensingmentioning

confidence: 99%

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Process defects andin situmonitoring methods in metal powder bed fusion: a review

Grasso

Colosimo

2017

Meas. Sci. Technol.

587

246

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“…15 In related studies “inline coherent imaging” has been used for process monitoring in selective laser melting (SLM). 16–18 Though quite similar to SLS in many ways, SLM uses metals with significant optical differences when compared to the polymers used in SLS processes. Whereas inline coherent imaging of metals yields surface topology, OCT imaging of polymers yields cross-sectional data for broader analysis potential.…”

Section: Introductionmentioning

confidence: 99%

In situ process monitoring in selective laser sintering using optical coherence tomography

et al. 2018

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Selective laser sintering (SLS) is an efficient process in additive manufacturing that enables rapid part production from computer-based designs. However, SLS is limited by its notable lack of in-situ process monitoring when compared to other manufacturing processes. We report the incorporation of optical coherence tomography into an SLS system in detail and demonstrate access to surface and sub-surface features. Video frame rate cross-sectional imaging reveals areas of sintering uniformity and areas of excessive heat error with high temporal resolution. We propose a set of image processing techniques for SLS process monitoring with OCT and report the limitations and obstacles for further OCT integration with SLS systems.

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“…Additionally, the layer-wise nature of the build process offers the opportunity to measure, assess, and even correct solidified structures at the layer level through deployment of surface morphology measurement techniques. Neef et al (2014) previously demonstrated the use of low-coherence interferometry to scan powder bed topology before and after laser processing. However, experiments were limited to static interfaces and did not investigate melt pool dynamics.…”

Section: Introductionmentioning

confidence: 99%

In situ morphology-based defect detection of selective laser melting through inline coherent imaging

Kanko

Sibley

Fraser

2016

Journal of Materials Processing Technology

164

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Low Coherence Interferometry in Selective Laser Melting

Cited by 72 publications

References 1 publication

Process defects andin situmonitoring methods in metal powder bed fusion: a review

Process defects andin situmonitoring methods in metal powder bed fusion: a review

In situ process monitoring in selective laser sintering using optical coherence tomography

In situ morphology-based defect detection of selective laser melting through inline coherent imaging

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