Evaluation of selective laser sintering processes by optical coherence tomography

Guan, Guangying; Hirsch, M.; Zeng, Lu; Childs, David; Matcher, Stephen J.; Goodridge, Ruth; Groom, K. M.; Clare, Adam T.

doi:10.1016/j.matdes.2015.09.084

Cited by 42 publications

(16 citation statements)

References 19 publications

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“…Another example of this workflow being employed is in the automotive industry where polymer based AM processes are used for interior trim applications [36]. A suitable in-situ measurement process, such as optical coherence tomography for selective laser sintering [37], could be used to inform on rework strategies in production for part quality optimisation in this highly aesthetic application. The long term aim of this work is to develop an automated system that is capable of the in-process identification, characterisation and rework of defects occurring in an SLM build.…”

Section: Resultsmentioning

confidence: 99%

Targeted rework strategies for powder bed additive manufacture

Hirsch

Dryburgh

Catchpole-Smith

et al. 2018

Additive Manufacturing

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A major factor limiting the adoption of powder-bed-fusion additive manufacturing for production of parts is the control of build process defects and the effect these have upon the certification of parts for structural applications. In response to this, new methods for detecting defects and to monitor process performance are being developed. However, effective utilisation of such methods to rework parts in process has yet to be demonstrated. This study investigates the use of spatially resolved acoustic spectroscopy (SRAS) scan data to inform repair strategies within a commercial selective laser melting machine. New methodologies which allow for rework of the most common defects observed in selective laser melting (SLM) manufacturing are proposed and demonstrated. Three rework methodologies are applied to targeted surface breaking pores: a hatch pattern, a spiral pattern and a single shot exposure. The work presented shows that it is possible to correct surface breaking pores using targeted re-melting, reducing the depth of defects whilst minimising changes in local texture. For the hatch rework and spiral rework, a reduction in defect depth of 50 % and 31 % were observed, respectively, however, no improvement was seen after the single shot exposures. This work is part of a programme to develop a method by which defects can be detected and the part reworked in-process during SLM to enable defect specification targets to be met. Although further work in developing build-characterise-rework strategies for integrated and targeted defect correction is needed, the feasibility of the underlying method of identifying and selectively reworking to reduce a defect has now been demonstrated for the first time.

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Section: Resultsmentioning

confidence: 99%

Targeted rework strategies for powder bed additive manufacture

Hirsch

Dryburgh

Catchpole-Smith

et al. 2018

Additive Manufacturing

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“…The method for the acquisition of a cross-sectional 2D structural image in AM specimens is described elsewhere [ 2 ]. OCT performs cross-sectional imaging by measuring the magnitude and echo time delay of backscattered light.…”

Section: Methodsmentioning

confidence: 99%

Loose powder detection and surface characterization in selective laser sintering via optical coherence tomography

et al. 2016

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Defects produced during selective laser sintering (SLS) are difficult to non-destructively detect after build completion without the use of X-ray-based methods. Overcoming this issue by assessing integrity on a layer-by-layer basis has become an area of significant interest for users of SLS apparatus. Optical coherence tomography (OCT) is used in this study to detect surface texture and sub-surface powder, which is un-melted/insufficiently sintered, is known to be a common cause of poor part integrity and would prevent the use of SLS where applications dictate assurance of defect-free parts. To demonstrate the capability of the instrument and associated data-processing algorithms, samples were built with graduated porosities which were embedded in fully dense regions in order to simulate defective regions. Simulated in situ measurements were then correlated with the process parameters used to generate variable density regions. Using this method, it is possible to detect loose powder and differentiate between densities of ±5% at a sub-surface depth of approximately 300 μm. In order to demonstrate the value of OCT as a surface-profiling technique, surface texture datasets are compared with focus variation microscopy. Comparable results are achieved after a spatial bandwidth- matching procedure.

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“…Other authors studied non-destructive inspection techniques suitable for metal AM discussing their possible usage for in-situ measurements. As an example, Guan et al (2015Guan et al ( -2016 studied the optical coherence tomography (OCT) technique to capture cross-sectional structural images of the part in order to characterize the surface and sub-surface part integrity. Guan et al (2015Guan et al ( -2016 pointed out the OCT devices could be integrated in laser-based PBF systems for in-situ monitoring.…”

Section: Off-axial Sensingmentioning

confidence: 99%

“…Indeed, the rapid development of optical sensor and computing technology enables real-time monitoring and control. One solution suggested by Guan et al (2015Guan et al ( -2016 consists of combining OCT with other detectors, e.g., high-speed cameras, to perform a rough scan. Once the area of interest has been located, the OCT can apply a higher resolution scan and provide a higher-detail evaluation of the sub-surface.…”

Section: Off-axial Sensingmentioning

confidence: 99%

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

Grasso

Colosimo

2017

Meas. Sci. Technol.

619

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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Evaluation of selective laser sintering processes by optical coherence tomography

Cited by 42 publications

References 19 publications

Targeted rework strategies for powder bed additive manufacture

Targeted rework strategies for powder bed additive manufacture

Loose powder detection and surface characterization in selective laser sintering via optical coherence tomography

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

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