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1.BackgroundAdditive manufacturing (AM) is a growing field with rapid industrial incorporation. Selective laser sintering (SLS) in particular is a promising technology for manufacturing parts that have been historically difficult to fabricate using classical machining techniques. SLS works by selectively sintering (melting) polymer powder beds layer by layer.1,2 After a melt pool is formed for the current layer of the part, a new layer of powder is spread over the entire build area, and the process is repeated. A complex part can thus be constructed in a layer-wise manner. The melt pool cools to form the solidified part, and the excess powder is removed. As SLS parts begin to be incorporated into devices with heavy governmental regulation (e.g., medical, aerospace) and higher performance, there is a need for precise and accurate feedback to inform the process. Monitoring the powder bed throughout the build can provide metrics on the health of the process and the quality of the part.3 In fact, several techniques have been proposed and adopted for powder bed monitoring: infrared imaging has been used to monitor surface temperature variations that can contribute to part inadequacies,4 and high-resolution visible wavelength imaging evaluates two-dimensional (2-D) errors in a layer-by-layer geometry both before5 and after6,7 the sintering process. Although these processes monitor each layer of the build, they do not offer subsurface information about the build. Optical coherence tomography (OCT) has recently been proposed to fill this gap. OCT is an optical imaging technique based on low coherence interferometry.8 OCT, as a light analog to ultrasound, offers wavelength-encoded depth information about a sample with 1- to axial resolution. This imaging technique is the standard of care in ophthalmology, where it is used for corneal and retinal imaging, and cardiology has also widely adopted the use of intravascular OCT for plaque visualization. One area of growth for OCT is in the manufacturing fields; recent publications have reported OCT systems for automobile paint assessment,9,10 quantitative touch-screen panel analysis,11 identification of glass defects,12 and the evaluation of polymer coatings for pharmaceutical pellets.13 OCT has been utilized recently to image SLS parts. Guan et al.14 demonstrated the utility of OCT for ex situ analysis of AM parts and discussed the possibility of in situ monitoring for polymers, outlining the significant potential for repair techniques, optimization processes, and material conservation. Correspondingly, we have previously reported both ex situ analysis and in situ implementation of OCT with SLS to illustrate its utility in resolving layers in sintered parts.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 with 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. In this paper, we present a thorough analysis of the optical design and recommendations of image processing protocols for video-rate cross-sectional analysis. We also report new findings on the variation of subsurface defects as a function of laser power. 2.Methods and Materials2.1.Optical DesignThe SLS optical design (Fig. 1) includes a laser (collimated output with a beam diameter of 4.2 mm), a Keplerian telescope for beam expansion () and an objective lens (, ) that focuses the light onto the build surface. The beam is directed by a pair of postobjective scanning galvanometers and enters the build chamber through a zinc selenide (ZnSe) window. The maximum area build surface is a circle with radius 109 mm; the radius of the build area is constrained by the size of the ZnSe window. A full description of the SLS system (Laser Additive Manufacturing Pilot System) can be found in Wroe et al.19 and Fish et al.20 The OCT system (Fig. 1) is a fiber-based Mach–Zehnder interferometer design with a swept source laser (, 100 kHz repetition rate, Axsun). The sample arm light (80%) is collimated to a 12-mm diameter by a reflective collimator and focused by a long focal-length objective lens (, ). The OCT beam is coaligned with the sintering beam using a dichroic mirror and is scanned by the same postobjective scanning galvanometers before the light enters the build chamber through the ZnSe window. Thus, the OCT beam and beam are always incident on the same location. The peak sensitivity of the system was experimentally determined to be 98.6 dB with an axial resolution of , and the system roll-off yielded an imaging range of 3.36 mm (Fig. 2). The OCT beam was incident on the sample with a power of 14.8 mW with a spot size of (radius) at the focal plane. 2.2.Part DesignTo examine the utility of OCT in detecting subsurface changes, an experimental protocol was developed in which the beam first sintered two reference points 4-cm apart on a nylon powder bed (2.5 W laser power for 0.1 s each). These marking holes assisted in identifying the beam location in the resultant OCT image. After these holes were formed, the beam sintered a 2.5-cm line directly between the two marking holes. This line was sintered in repeating experiments with a range of laser powers (20%, 40%, 60%, 80%, and 100%). For each experiment, the OCT system captured a series of A-scans at 100 kHz during each of these sintering steps and continued to collect B-scan images of the sintered area for after the nylon was sintered to monitor surface and subsurface variation (Fig. 3). 2.3.Image ProcessingWe process the OCT images using two processing phases to improve the signal-to-noise ratio (SNR)21 for enhanced image analysis. First, we developed a “second-order interleaving” process. Using this new image processing approach for OCT samples with low light penetration depths, every second data point in each A-scan fringe was taken to form two A-scans fringes from the same A-scan location (1, 3, 5, …, 1375 and 2, 4, 6, …, 1376). The resulting two A-scans were averaged to improve the SNR. Because the penetration depth of 1310-nm light in nylon is less than half of our imaging range (3.7 mm), the OCT signal from the build surface was isolated to low-frequency fringe patterns. Thus, though the imaging range is halved by second-order interleaving, the build surface topology was maintained in both A-scans. After interleaving for improved SNR, the contrast was adjusted and a block matching three-dimensional (BM3D) filter22 applied. A second phase corrects the image for the effects of field curvature. The nylon surface in the B-scan exhibits a hyperbolic curve because of postobjective scanning and a fixed reference arm. To correct for this curvature, the top surface of the B-scan is detected using standard edge-detection algorithms and then fit to a second-order polynomial, approximating the hyperbolic curvature close to the turning point. Then, pixels are shifted (with interpolation) to make the top surface horizontal. The bottom surface of the melt pool was found by a second edge-detection algorithm. Finally, the melt pool depth was calculated by the mean distance from the top surface, and the excessive heat error was recorded as the max distance of the melt pool edge from the melt pool mean depth (Fig. 4). 3.ResultsThe incorporated SLS+OCT design observed subsurface melt pool changes that were previously only inferred by 2-D en face imaging and postprocessing analysis. The OCT images reveal the top surface of the nylon powder and the top and bottom surface of the melt pool. The OCT images also show subsurface flaws in the build due to excessive heating. As the laser power increased from 20% (4.6 W) to 100% (32.5 W), the average melt pool depth increased monotonically from 0.01 to 0.17 mm. Additionally, a defect area of increased melt pool depth was observed at the temporally distal end of the scan (the right edge of the melt pool). This “excessive heat error” (maximum depth as measured from the average melt pool depth) also increased monotonically as a function of laser power from an average of 0.02 to 0.12 mm (Fig. 5 and Video 1). 4.DiscussionIt was anticipated that greater sintering laser powers would yield a deeper melt pool because of a larger temperature gradient. However, as mentioned in the results section, the OCT system detected “excessive heat error” that illustrates the utility of a three-dimensional imaging approach and OCT in particular. Near the right edge of the sintered area a defect area became apparent at low laser powers and increasingly more remarkable at higher laser powers. The defect occurred where the sintering laser was turned off to stop the sintering process. It is probable that this defect is due to a slight dissimilarity in the amount of energy deposited into the powder (excessive heat), either by a sudden increase in laser power as the laser is turned off, or more likely, a deceleration, or lingering of the galvanometer scanning at the “turn off” location due to galvanometer constraints. With these images as feedback, laser power could be responsively varied to minimize this excessive heat error. Field curvature limited the build area for OCT imaging. Due to the OCT system’s imaging depth, any surface that had a pathlength difference of was aliased in the OCT fringe as a low-frequency component and thus unreliable for interpretation. With the field curvature induced by postobjective scanning and the OCT system’s imaging depth, the build area is limited to a circle with a 64-mm radius, where the center point appears as the shortest pathlength difference (distance 0, 0 in Fig. 6) and the edges are the longest pathlength difference. Down-sampling for second-order interleaving further limited the field of view to a circle with 45-mm radius (blue inner circle in Fig. 6). In the present iteration, the OCT beam and the sintering beam are coaligned and share the same galvanometer mirrors. This limits any live imaging to the current sintering location. The experiment performed in this study revealed postsintering time points by scanning the galvanometer mirrors across the sintered area after the sintering laser turned off. However, including a “fast scan” galvanometer in the OCT beam path before the shared galvanometers would enable imaging of areas around the instantaneous location of the sintering beam. Future studies could advance the utility of SLS + OCT by recording the absolute temperature of the polymer surface during the build. Although the LAMPS system had been previously equipped with an IR camera for temperature monitoring,19,23 the reported OCT system used the same dichroic and thus precluded simultaneous IR and OCT monitoring. With an additional dichroic, the correlation of OCT data with the absolute temperature could prove useful in building a database of common depth-resolved errors with certain surface temperature profiles. Rapid, real-time processing is necessary for a live feedback mechanism and responsive defect correction. Real-time processing was not the aim of this study, but this work lays out potential processing pathways for interpreting OCT data for such mechanisms. 5.ConclusionsAn OCT imaging system was incorporated into an SLS machine. The data show that OCT can detect subsurface defects with micron resolution. 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