Browsing by Subject "in-situ monitoring"
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Item Conditional Generative Adversarial Networks for In-Situ Layerwise Additive Manufacturing Data(University of Texas at Austin, 2019) Gobert, Christian; Arrieta, Edel; Belmontes, Adrian; Wicker, Ryan B.; Medina, Francisco; McWilliams, BrandonConditional generative adversarial networks (CGANs) learn a mapping from conditional input to observed image and perform tasks in image generation, manipulation and translation. In-situ monitoring uses sensors to obtain real-time information of additive manufacturing (AM) processes that relate to process stability and part quality. Understanding the correlations between process inputs and in-situ process signatures through machine learning can enable experimental-driven predictions of future process inputs. In this research, in-situ data obtained during a metallic powder bed fusion AM process is mapped with a CGAN. A single build of two turbine blades is monitored using EOSTATE Exposure OT, a near-infrared optical tomography system of the EOS M290 system. Layerwise images generated from the in-situ monitoring system were paired with a conditional image that labeled the specimen cross-section, laser-scan stripe overlap and z-distance to part surfaces. A CGAN was trained using the turbine blade data set and employed to generate new in-situ layerwise images for unseen conditional inputs.Item In-Process Condition Monitoring in Laser Powder Bed Fusion (LPBF)(University of Texas at Austin, 2017) Montazeri, Mohammad; Rao, PrahaladaThe goal of this work is to monitor the laser powder bed fusion (LPBF) process using an array of heterogeneous sensors. This goal is termed as build status monitoring. The overarching aim is to usher a qualify-as-you-build quality assurance paradigm in LPBF whereby incipient build defects are detected through analysis of data acquired from in-process sensors. This will allow opportune preventive action to avert propagation of build defects across multiple layers. In pursuit of this goal, a commercial LPBF machine at the National Institute of Standards and Technology (NIST) was integrated with three types of sensors, namely, a photodetector, high-speed video camera, and SWIR thermal camera with the following objective: to develop and apply a spectral graph theoretic approach to monitor the LPBF build status from the data acquired by the three sensors. This objective will lead to early identification of incipient defects that afflict LPBF despite extensive process automation. The proposed approach is illustrated with experimental sensor data acquired during LPBF of a part having a steep overhang feature of ~ 40.5o . Parts with such steep overhang features may exacerbate deleterious consequences such as poor surface finish, porosity, and distortion. Hence, close monitoring of the signal patterns during scanning of overhang areas is consequential for early detection of build defects. The proposed approach detected differences between overhang and non-overhang build status for different sensors with the statistical fidelity (F-score) of 95% from thermal camera signatures to 79% with the photodetector. In comparison, conventional signal analysis techniques - e.g., neural networks, support vector machines, linear discriminant analysis, etc., are evaluated with F-score in the range of 40% to 60%. As part of our forthcoming work, this study will be further expanded to include more build defects, e.g., due to material contamination.Item In-Situ Non-Destructive Evaluation of Ultrasonic Additive Manufactured Components(University of Texas at Austin, 2016) Nadimpalli, Venkata Karthik; Na, Jeong K.; Bruner, Darren T.; King, Brenna A.; Yang, Li; Stucker, Brent E.In-situ monitoring of Ultrasonic Additive Manufacturing (UAM) process is crucial for producing parts suitable for load-bearing structural applications. Due to the nature of UAM process, it is necessary to monitor the entire build as opposed to only the just bonded layer. For this purpose, an ultrasonic transducer is used in this study to perform in-situ nondestructive evaluation (NDE) of the entire build after the addition of each new layer. This has been successfully implemented first on a manually operated research UAM machine and then applied on a fully automated commercial grade UAM machine. The practical applications of such in-situ measurements for ensuring defect-free part fabrication through closed-loop control of the UAM process control is shown to be possible from the results of this work.Item INVESTIGATION OF INSTRUMENTING ROBOCASTING PRINTER FOR CERAMIC SLURRIES(University of Texas at Austin, 2023) McCleary, J.; Durand, N.; Castillo Perez, L.; Medina Zorrosa, G.; Garcia Chavira J.P.; Espalin, D.Robocasting has multiple steps from ceramic slurry preparation to sintering that can impact the end part quality. In-situ monitoring and process controls can aid in minimizing differences in the quality of printed parts. The study and impact of different parameters during the printing process and a parameter database will improve the quality between green bodies and sintered parts. This paper discusses implementation of a CMOS camera, dynamic pressure sensor, and 2D laser scanner into a custom-built robocasting printer for in process monitoring. Single line beads were printed and analyzed by measuring the dimensions and pressure changes during printing. Results show that the printer with sensors detected the location of possible defects and changes in printed samples but further investigation is needed to filter noise and collect conclusive data.Item Laser Induced Breakdown Spectroscopy for In-Situ Monitoring of Laser Powder Bed Fusion Processing(University of Texas at Austin, 2023) Krantz, Justin T.; Lough, Cody S.; Brown, Ben; Yang, Jinyu; Go, David B.; Landers, Robert G.; Kinzel, Edward C.A major challenge for laser powder bed fusion processes is identifying and addressing flaws in the as-built part. In-situ monitoring of the magnitude of radiation emitted from the vicinity of the melt pool largely corresponds to the temperature field. This has been correlated with the local porosity and microstructure of the part. However, the composition of the part can also vary, either because of processing conditions or differences in the powder. Spectroscopy has the potential to resolve material composition because spectral lines corresponding to atomic species present in the metal can be clearly observed. The line emission phenomena from ionization and excitation in the vapor plume is limited under standard LPBF conditions. Laser induced breakdown spectroscopy (LIBS) uses a pulsed laser to produce a localized plasma. This is demonstrated in LPBF using an ultrashort pulsed (USP) laser coaligned to the continuous wave (CW) process laser. The USP laser can be used to probe the melt pool and plume in-process, creating a plasma that is independent of the process conditions. This probing process has minimal adverse effects on the melt pool. LIBS can provide feedback about the local species content through time resolved spectroscopy and provides the potential for voxelwise composition information to be obtained from the material.Item Process Modeling and In-Situ Monitoring of Photopolymerization for Exposure Controlled Projection Lithography (ECPL)(University of Texas at Austin, 2017) Wang, J.; Zhao, C.; Zhang, Y.; Jariwala, A.; Rosen, D.Exposure controlled projection lithography (ECPL) is an additive manufacturing process in which photopolymer resin is used to fabricate three-dimensional features. During this process, UV curing radiation, controlled by a dynamic mask, is projected through a transparent substrate onto the resin. COMSOL software has been used to model the photopolymerization reaction kinetics, predicting the cured part geometry based on certain process parameters. Additionally, an Interferometric Curing Monitoring (ICM) system has been implemented to acquire real-time information about the optical properties of the cured part. Potential sources of error with the real-time monitoring system were investigated. Additionally, refractive index and degree of conversion changes were modeled throughout the reaction. Measured and simulated results were compared to understand the ICM signal with the reaction kinetics. These comparisons were used to validate the simulation model and identify system level errors that must be reconciled to improve the accuracy and precision of the ECPL process.Item Rheological, In Situ Printability and Cell Viability Analysis of Hydrogels for Muscle Tissue Regeneration(University of Texas at Austin, 2018) Ramesh, Srikanthan; Gerdes, Sam; Lau, Sharon; Mostafavi, Azadeh; Kong, Zhenyu; Johnson, Blake N.; Tamayol, Ali; Rao, Prahalada; Rivero, Iris V.Advancements in additive manufacturing have made it possible to fabricate biologically relevant architectures from a wide variety of materials. Hydrogels have garnered increased attention for the fabrication of muscle tissue engineering constructs due to their resemblance to living tissue and ability to function as cell carriers. However, there is a lack of systematic approaches to screen bioinks based on their inherent properties, such as rheology, printability and cell viability. Furthermore, this study takes the critical first-step for connecting in-process sensor data with construct quality by studying the influence of printing parameters. Alginate-chitosan hydrogels were synthesized and subjected to a systematic rheological analysis. In situ print layer photography was utilized to identify the optimum printing parameters and also characterize the fabricated three-dimensional structures. Additionally, the scaffolds were seeded with C2C12 mouse myoblasts to test the suitability of the scaffolds for muscle tissue engineering. The results from the rheological analysis and print layer photography led to the development of a set of optimum processing conditions that produced a quality deposit while the cell viability tests indicated the suitability of the hydrogel for muscle tissue engineering applications.Item Role of In-situ Monitoring Technique for Digital Twin Development using Direct Energy Deposition: Melt Pool Dynamics and Thermal Distribution(University of Texas at Austin, 2023) Wu, Sung-Heng; Joy, Ranjit; Tariq, Usman; Mahmood, Muhammad Arif; Liou, FrankDirect energy deposition (DED) is a promising additive manufacturing technique that enables the fabrication of complex structures with excellent mechanical properties. The quality of the final product depends on several parameters, including melt pool dynamics and thermal distribution. For process monitoring and continuous improvement of digital twins, in-situ monitoring allows real-time tracking of these parameters, providing valuable data for process optimization. However, existing monitoring methods are limited in their accuracy due to emissivity issues. To address this challenge, an in-house visible spectrum camera has been proposed for real-time process monitoring via dual-wavelength technique. Based on the analyses, the area and thermal distribution inside the melt pool can be estimated accurately. The data from the camera can be integrated into a digital twin’s continuous improvement, providing efficiency, and reducing the manufacturing cost.Item Thermal History Correlation with Mechanical Properties for Polymer Selective Laser Sintering (SLS)(University of Texas at Austin, 2017) Taylor, Samantha; Beaman, Joseph; Fish, ScottThis study investigates the in-situ monitoring of the Selective Laser Sintering (SLS) process by focusing on finding correlations between tensile strength, elongation to break, and fracture location to the observed thermal history of manufactured parts. It compared the monitoring ability of a stationary reference mid-wave infrared and a bore-sighted mid-wave infrared camera. ZYX tensile bars were built to leverage the high dependence of tensile strength on interlayer bonding, which is generally assumed to be related to layerwise thermal conditions. Various thermal history analysis methods, for example: cold subregion temperature, average layer temperature, and outline average temperature were tested. Additionally, several smoothing techniques that reduced noise over time were assessed for their ability to improve the correlation for each individual method. Overall, cold subregions observed over four layers in a tensile bar’s thermal history had the best correlation with fracture location and mechanical strength.