Laser Line Scan Characterization of Geometric Profiles in Laser Metal Deposition

Laser Metal Deposition (LMD) is an additive manufacturing process in which material is deposited by blowing powdered metal into a melt pool formed by a laser beam. When fabricating parts, the substrate is subjected to motion control such that the melt pool traces a prescribed path to form each part layer. Advantages of LMD include relatively efficient powder usage, the ability to create functionally-graded parts and the ability to repair high-value parts. The process, however, is sensitive to variations in process parameters and a need for feedback measurements and closed-loop control has been recognized in the literature [1, 2]. To this end, a laser line scanner is being integrated into an LMD system at the Missouri University of Science and Technology. Measurements from the laser line scanner will provide the feedback data necessary for closed-loop control of the process. The work presented here considers characteristics of the laser line scanner as it relates to scanning LMD depositions. Errors associated with the measurement device are described along with digital processing operations designed to remove them. The parameter bead height is extracted from scans for future use in a closed-loop control strategy

A Loop-Shaping Method for Frequency-Based Design of Layer-To-Layer Control for Laser Metal Deposition

Additive manufacturing processes fabricate parts in a layer-by-layer fashion, depositing material along a predefined path before incrementing to the next layer. Although the thickness of any given layer is bounded, in-layer dynamics can couple with layer-to-layer dynamics such that height defects amplify from one layer to the next. This is considered instability in the layer domain. By considering each layer as an iteration, additive processes can be categorized as repetitive processes. Although Repetitive Process Control (RPC) algorithms exist that can stabilize the process and converge to desired reference, it is typically assumed that the reference and disturbance are constant from layer to layer. In this paper, the problem of tracking references (layer thicknesses) that change from layer to layer is considered. The bandwidth of the changing references is considered bounded in both the spatial and layer domains. A loop-shaping design process is then considered, in which the bounds are mapped to a bound on the two-dimensional sensitivity function and projected onto weighting filters in an LQR control formulation. The layer-to-layer controller is then constructed from traditional LQR methods. The controller is demonstrated on a simulation of laser metal deposition for a wavy wall build having frequency content in both the spatial and layer domains

Model Predictive Height Control for Direct Energy Deposition

Direct energy deposition (DED) is a metal additive process that has applications in high-value part repair and fabrication of functionally-graded parts. However, the process is sensitive to commanded inputs and process conditions, such as powder flow and heat conduction from the melt pool, which change throughout the course of a build and often lead to geometric inaccuracies in the final part. Thus, there is a need for in-process sensing and feedback control to improve robustness to process conditions and achieve the desired part geometry. Previously, a repetitive process, quadratic-optimal height controller was implemented on thin-wall builds, where height measurements and control updates were performed in between layers. In that work, the desired layer thickness remained constant from layer to layer. Here, the repetitive process framework is extended to account for height references that change with layer number, as will be the case for producing more complex part geometries. Using this extended model, a model predictive controller is derived and simulated on a part build with iteration-varying references

Repetitive Process Control of Additive Manufacturing With Application to Laser Metal Deposition

Additive manufacturing (AM) is a set of manufacturing processes that have promise in the production of complex, functional structures that cannot be fabricated with conventional manufacturing, and in the repair of high-value parts. However, a significant challenge to the adoption of AM processes to these applications is proper process control. Because AM processes exhibit dynamics in two dimensions--within a layer and from one layer to the next--unconventional tools are needed to enable the necessary process control. Here, stability analysis and control design are presented for the laser metal deposition (LMD) process, based on a previously developed 2-D modeling framework. Linear repetitive process results are extended in order to analyze the stability of this class of systems. A layer-to-layer process controller is developed using a spatial dynamic model of the process and layer-domain closed-loop poles. The stability analysis and control methodology are applied to the LMD process, which is known to exhibit layer-to-layer instability in both open-loop and in-process control depositions. Walls are experimentally fabricated using constant process parameters and the proposed control methodology. The results demonstrate that the proposed control methodology is able to track the reference height and remove the unstable ripple dynamic that naturally occurred in the open-loop deposition

Repetitive Process Control of Additive Manufacturing with Application to Laser Metal Deposition

Additive manufacturing (AM) is a set of manufacturing processes that have promise in the production of complex, functional structures that cannot be fabricated with conventional manufacturing, and in the repair of high-value parts. However, a significant challenge to the adoption of AM processes to these applications is proper process control. Because AM processes exhibit dynamics in two dimensions--within a layer and from one layer to the next--unconventional tools are needed to enable the necessary process control. Here, stability analysis and control design are presented for the laser metal deposition (LMD) process, based on a previously developed 2-D modeling framework. Linear repetitive process results are extended in order to analyze the stability of this class of systems. A layer-to-layer process controller is developed using a spatial dynamic model of the process and layer-domain closed-loop poles. The stability analysis and control methodology are applied to the LMD process, which is known to exhibit layer-to-layer instability in both open-loop and in-process control depositions. Walls are experimentally fabricated using constant process parameters and the proposed control methodology. The results demonstrate that the proposed control methodology is able to track the reference height and remove the unstable ripple dynamic that naturally occurred in the open-loop deposition

Scalable Nanomanufacturing of Metasurfaces using Nanosphere Photolithography

We report on using Nanosphere Photolithography (NPL) for submicron patterning of Frequency Selective Surfaces (FSS). NPL is a combination of two techniques; colloidal nanolithography-where nanospheres form a self-assembled hexagonal close-packed (HCP) array when dispensed on a surface, and photonic jets-which are created when light is incident onto a microsphere in contact with a surface. NPL creates a mask-free HCP hole array in the photoresist. This pattern can be used with evaporation and lift-off to create an array of antenna elements, constituting the FSS. Alternatively, electrodeposition techniques can be used to deposit the metal elements. The later is particularly appealing as it lends itself to reel-to-reel fabrication techniques. Finally, we demonstrate that geometries other than simple hole arrays can be patterned in the photoresist by exposing the microsphere array with off normal incidence light

Modal Response as a Validation Technique for Metal Parts Fabricated with Selective Laser Melting

This paper investigates modal analysis as a validation technique for additively manufactured parts. The Frequency Response Function (FRF) is dependent on both the geometry and the material properties of the part as well as the presence of any defects. This allows the FRF to serve as a “fingerprint” for a given part of given quality. Once established, the FRF can be used to qualify subsequently printed parts. This approach is particularly attractive for metal parts, due to the lower damping as well as use in high-value applications where failure is unacceptable. To evaluate the efficacy of the technique, tensile specimens are printed with a Renishaw AM250, the modal response of these parts is characterized prior to tensile testing, and the FRFs are compared to their engineering metrics for parts printed with both nominal and off-nominal parameters. Numerical modeling is used to understand the modal structure, and the possibility of defect prognosis is also explored by comparing the measured response to simulation results.Mechanical Engineerin