In situ quality control of the selective laser melting process using a high-speed, real-time melt pool monitoring system

Clijsters, Stijn; Craeghs, Tom; Buls, Sam; Kempen, Karolien; Kruth, Jean‐Pierre

doi:10.1007/s00170-014-6214-8

Cited by 373 publications

(176 citation statements)

References 11 publications

(9 reference statements)

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“…Differently, contour followed or following by hatch can vary from research to research [98,99]. And the contour is generally associated with lower power and lower scanning speed to improve the geometry accuracy and roughness, while the hatch is adjusted to higher power and higher scanning speed to increase the productivity [98,100].…”

Section: Processmentioning

confidence: 99%

Additively Manufactured Inconel 718 : Microstructures and Mechanical Properties

Deng

2018

Linköping Studies in Science and Technology. Licentiate Thesis

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Linköping 2018Cover image: A fracture surface of EBM IN718 after tensile test at room temperature.During the course of research underlying this thesis, Dunyong Deng was enrolled in Agora Materiae, a multidiciplinary doctoral program at Linköping University, Sweden. Printed by LiU-Tryck 2018 © Dunyong Deng AbstractAdditive manufacturing (AM), also known as 3D printing, has gained significant interest in aerospace, energy, automotive and medical industries due to its capabilities of manufacturing components that are either prohibitively costly or impossible to manufacture by conventional processes. Among the various additive manufacturing processes for metallic components, electron beam melting (EBM) and selective laser melting (SLM) are two of the most widely used powder bed based processes, and have shown great potential for manufacturing high-end critical components, such as turbine blades and customized medical implants. The futures of the EBM and SLM are doubtlessly promising, but to fully realize their potentials there are still many challenges to overcome.Inconel 718 (IN718) is a nickel-base superalloy and has impressive combination of good mechanical properties and low cost. Though IN718 is being mostly used as a turbine disk material now, the initial introduction of IN718 was to overcome the poor weldability of superalloys in 1960s, since sluggish precipitation of strengthening phases γ ′ /γ ′′ enables good resistance to strain-age cracking during welding or post weld heat treatment. Given the similarity between AM and welding processes, IN718 has been widely applied to the metallic AM field to facilitate the understandings of process-microstructure-property relationships.The work presented in this licentiate thesis aims to better understand microstructures and mechanical properties EBM and SLM IN718, which have not been systematically investigated. Microstructures of EBM and SLM IN718 have been characterized with scanning electron microscopy (SEM), transmission electron microscopy (TEM) and correlated with the process conditions. Monotonic mechanical properties (e.g., Vickers microhardness and tensile properties) have also been measured and rationalized with regards to the microstructure evolutions before and after heat treatments.For EBM IN718, the results show the microstructure is not homogeneous but dependant on the location in the components, and the anisotropic mechanical properties are probably attributed to alignment of porosities rather than texture.iii Post heat treatment can slightly increase the mechanical strength compared to the as-manufactured condition but does not alter the anisotropy. SLM IN718 shows significantly different microstructure and mechanical properties to EBM IN718. The as-manufactured SLM IN718 has very fine dendritic microstructure and Laves phases in the interdendrites, and is "work-hardened" by the residual strains and dislocations present in the material. Mechanical properties are different between horizontally and vertically built samples, and heat treatment can m...

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Section: Processmentioning

confidence: 99%

Additively Manufactured Inconel 718 : Microstructures and Mechanical Properties

Deng

2018

Linköping Studies in Science and Technology. Licentiate Thesis

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“…The revised edition of the above system combines imaging sensors with an external illumination of the interaction zone and its neighborhood for high resolved pictures at high scanning velocities to capture the surface structure and the melt pool dynamics [81]. High-speed near-infrared thermal CMOS camera and a photodiode coaxial with the laser beam ensure a high quality measurement of the melt pool, while the data analysis system to translate and visualize measured sensor values in the format of interpretable process quality images [82].…”

Section: Sensor-based Process Monitoring In Additive Manufacturingmentioning

confidence: 99%

Integration of physically-based and data-driven approaches for thermal field prediction in additive manufacturing

Jin

2018

Materials & Design

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A quantitative understanding of thermal field evolution is vital for quality control in additive manufacturing (AM). Because of the unknown material parameters, high computational costs, and imperfect understanding of the underlying science, physically-based approaches alone are insufficient for component-scale thermal field prediction. Here, I present a new framework that integrates physically-based and data-driven approaches with quasi in situ thermal imaging to address this problem. The framework consists of (i) thermal modeling using 3D finite element analysis (FEA), (ii) surrogate modeling using functional Gaussian process, and (iii) Bayesian calibration using the thermal imaging data. Based on heat transfer laws, I first investigate the transient thermal behavior during AM using 3D FEA. A functional Gaussian process-based surrogate model is then constructed to reduce the computational costs from the high-fidelity, physically-based model. I finally employ a Bayesian calibration method, which incorporates the surrogate model and thermal measurements, to enable layer-to-layer thermal field prediction across the whole component. A case study on fused deposition modeling is conducted for components with 7 to 16 layers. The cross-validation results show that the proposed framework allows for accurate and fast thermal field prediction for components with different process settings and geometric designs. Integration of Physically-based and Data-driven Approaches for Thermal Field Prediction in Additive ManufacturingJingran Li GENERAL AUDIENCE ABSTRACT This paper aims to achieve the layer to layer temperature monitoring and consequently predict the temperature distribution for any new freeform geometry. An engineering statistical synergistic model is proposed to integrate the pure statistical methods and finite element modeling (FEM), which is physically meaningful as well as accurate for temperature prediction. Besides, this proposed synergistic model contains geometry information, which can be applied to any freeform geometry. This paper serves to enable a holistic cyber physical systems-based approach for the additive manufacturing (AM) not only restricted in fused deposition modeling (FDM) process but also can be extended to powder-based process like laser engineered net shaping (LENS) and selective laser sintering (SLS). This paper as well as the scheduled future works will make it affordable for customized AM including customized geometries and materials, which will greatly accelerate the transition from rapid prototyping to rapid manufacturing. This article demonstrates a first evaluation of engineering statistical synergistic model in AM technology, which gives a perspective on future researches about online quality monitoring and control of AM based data fusion principles. iv ACKNOWLEDGEMENTS

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“…Optical methods are the easiest to use during experimentation, as they are usually non-disruptive to the process and can be applied externally without modifying the process or equipment. A number of excellent optimal monitoring systems has been developed, in particular those by Craeghs et al [98][99][100][101], Kleszczynski et al [119], Clijsters et al [120], Chivel [121], Grasso et al [122], Hirsh et al [123], Kanko et al [124] and Lott et al [125]. Infrared thermography systems for SLM/DMSL have been developed by Rodriguez et al [126] and Smurov et al [127].…”

Section: Optical Process Monitoringmentioning

confidence: 99%

Overhanging Features and the SLM/DMLS Residual Stresses Problem: Review and Future Research Need

2017

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Abstract:A useful and increasingly common additive manufacturing (AM) process is the selective laser melting (SLM) or direct metal laser sintering (DMLS) process. SLM/DMLS can produce full-density metal parts from difficult materials, but it tends to suffer from severe residual stresses introduced during processing. This limits the usefulness and applicability of the process, particularly in the fabrication of parts with delicate overhanging and protruding features. The purpose of this study was to examine the current insight and progress made toward understanding and eliminating the problem in overhanging and protruding structures. To accomplish this, a survey of the literature was undertaken, focusing on process modeling (general, heat transfer, stress and distortion and material models), direct process control (input and environmental control, hardware-in-the-loop monitoring, parameter optimization and post-processing), experiment development (methods for evaluation, optical and mechanical process monitoring, imaging and design-of-experiments), support structure optimization and overhang feature design; approximately 143 published works were examined. The major findings of this study were that a small minority of the literature on SLM/DMLS deals explicitly with the overhanging stress problem, but some fundamental work has been done on the problem. Implications, needs and potential future research directions are discussed in-depth in light of the present review.

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In situ quality control of the selective laser melting process using a high-speed, real-time melt pool monitoring system

Cited by 373 publications

References 11 publications

Additively Manufactured Inconel 718 : Microstructures and Mechanical Properties

Additively Manufactured Inconel 718 : Microstructures and Mechanical Properties

Integration of physically-based and data-driven approaches for thermal field prediction in additive manufacturing

Overhanging Features and the SLM/DMLS Residual Stresses Problem: Review and Future Research Need

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