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We investigated the sensitivity of ultrasonic measurements to changes in the operating conditions during additive fabrication for 316L stainless steel samples by selective laser melting. We found that the velocity of the ultrasound propagation positively correlates with the energy density used to melt layers of metal powder during the fabrication....
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... S1 segments of the other two samples were fabricated with the same power density. Sections S2, S3, and S4 of the second sample (referred to as V+ sample) were printed with the beam power and scanning rate adjusted to increase the energy densities by 3 J/mm 3 for each new section (Table 1). The V-sample was fabricated by reducing the power density by the same 3 J/mm 3 in different segments in the build direction. ...Similar publications
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Powder Bed Fusion of Metals using a Laser Beam (PBF-LB/M) is increasingly utilized for the fabrication of complex parts in various industrial sectors. Enabling a robust and reproducible manufacturing process is one of the main goals in view of the future success of PBF-LB/M. To meet these challenges, alloys that are specifically adapted to the proc...
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Citations
... Scholars are presently engaged in the development of laser ultrasonic technology for the purposes of defect detection, material characterization, and performance evaluation. [5]- [9] Furthermore, it is crucial to consider the dispersion properties of the laser ultrasonic lamb wave when assessing the ability to characterize the thickness of thin specimens. The SLM process involves a layer-by-layer stacking formation, and the specimens produced undergo a transition from thin to thick. ...
Selective laser melting (SLM) technology, employed in metal additive manufacturing, is widely utilised to fabricate components with precise dimensions and excellent mechanical properties by melting powder layer by layer. Laser ultrasonic testing is anticipated to be an efficient method for in-line monitoring in the additive manufacturing (AM) process. The conversion of specimens from thin to thick during the SLM manufacturing process has an impact on the ultrasonic signals. This paper focuses on the influence of AM specimen thickness changes on ultrasonic signals. In the finite element analysis, the incremental specimen thickness was maintained at 0.2 mm, which was the initial value. As the specimen thickness increased sequentially, ultrasonic signals were obtained from different specimens. The results demonstrate that Lamb waves are generated when the specimen is thin, and the dispersive characteristics weaken as the thickness increases. The dispersive phenomenon diminishes significantly once the specimen thickness exceeds 1 mm. By employing the f-k method, calculated dispersion curves for various specimen thicknesses were obtained. After fitting the derived dispersion curve, a mapping relationship is established with respect to the specimen thickness. Consequently, the fitting coefficient of the dispersion curve can therefore be utilized to characterize the thickness of the additive manufactured thin specimen.
Successful production of metallic selective laser melting components requires a quality assurance process that can effectively and nondestructively assess internal defects. Ultrasound testing has emerged as a valuable modality for defect identification as well as the characterization of microstructural and material properties. In this study, a comprehensive quality assessment approach was developed, leveraging quantitative ultrasound parameters, images, and image texture analysis. The evaluation focused on Inconel 718 selective laser melting components manufactured using diverse combinations of process parameters. The investigation involved examining the correlation between ultrasound parameters, image texture features, and the overall quality of the fabricated components. To validate the findings obtained through ultrasound testing, micro-computed tomography was employed. The experimental results provided evidence that the ultrasound parameters and image texture features successfully detected nonhomogeneous microstructures present within the selective laser melting components. Notably, the speed of sound and attenuation exhibited a positive correlation with porosity, indicating their potential as indicators of porosity. Furthermore, the image texture features, including entropy, contrast, and homogeneity, demonstrated high correlations with the quality of the components. Consequently, these identified features hold promising potential for aiding in the selection of optimal process parameters and the prediction of porosity in future research.
Additive manufacturing is based on high-precision material deposition to build a final part or component by using various techniques. It is being one of the main advances in the fourth industrial revolution. This type of manufacturing is not new, although it is growing. There are many types of additive manufacturing techniques, and the use of efficient inspection methods to ensure a certain level of quality, and to detect faults, porosities, etc., are required in the industry. Nondestructive Testing is widely applied, and particularly in additive manufacturing, to ensure efficient quality control and preventive/predictive maintenance without changing the characteristics and initial state of the material. Each Nondestructive Testing technique is based on different physical principles; therefore, the selection and correct use of each technique depends on the application, the manufacturing process, the type of material and the possible discontinuities, among many others. This article develops a complete, exhaustive, and updated review and analysis of the state of the art of Nondestructive Testing applied in additive manufacturing. The main characteristics of the processes are analyzed, highlighting the most relevant works and the challenges that each technique should face. An analysis of techniques necessary for the development of Nondestructive Evaluation has been carried out, mainly Machine Learning techniques used for the quantification, detection and analysis of defects detected by Nondestructive Testing techniques.
The use of metal additive manufacturing (AM) technologies is growing rapidly in many industries owing to their ability to produce complex designs, to light-weight critical components, and to consolidate assemblies. Laser powder bed fusion (LPBF) is a metal AM technology that offers finer feature resolution when compared with other metal AM technologies, with ongoing challenges in controlling the process to guarantee defect-free parts. Manufacturing of end-use products via LPBF with a high degree of internal feature design complexity results in an increased demand for demonstrating the performance of various nondestructive evaluation (NDE) tools. In this work, the use of high-frequency (50 MHz) phased array ultrasonic testing (PAUT) for the nondestructive evaluation of a cubic AlSi10Mg sample manufactured by the LPBF process is demonstrated. Artificial internal features with various sizes and shapes are implanted into this sample. The sample is tested offline by high-frequency PAUT from different directions and the position and shape of defects are evaluated. The sample is then subjected to X-ray computed tomography (XCT) and the results are compared with those obtained by ultrasonic testing. Very good agreement is observed between PAUT and XCT results and defects with dimensions as small as 0.75 mm are successfully identified.
