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1. An Empirical Model and Feedforward Control of Laser Powder Bed Fusion

   https://doi.org/10.1115/1.4064171  

   Shkoruta, Aleksandr; Park, Bumsoo; Mishra, Sandipan (October 2023, ASME Letters in Dynamic Systems and Control)

   Reliable process control for the laser powder bed fusion process, especially at the melt pool scale, remains an open challenge. One of the reasons for this is the lack of suitable control-oriented models and associated control design strategies. To address this issue, this paper (1) identifies an empirical control-oriented model of geometry-dependent melt pool behavior and (2) experimentally demonstrates melt pool regulation with a feedforward controller for laser power based on this model. First, the study establishes that the melt pool signature increases as the scan lines decrease in length. An empirical model of this behavior is developed and validated on different geometries at varying laser power levels. Second, the model is used to design a line-to-line feedforward controller that provides an optimal laser power sequence for a given geometry. Finally, this controller is validated experimentally and is demonstrated to suppress the in-layer geometry-related melt pool signal deviations for different test geometries 

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2. Closed-Loop High-Fidelity Simulation Integrating Finite Element Modeling With Feedback Controls in Additive Manufacturing

   https://doi.org/10.1115/1.4048364  

   Wang, Dan; Chen, Xu (February 2021, Journal of Dynamic Systems, Measurement, and Control)

   null (Ed.)

   Abstract A high-precision additive manufacturing (AM) process, powder bed fusion (PBF) has enabled unmatched agile manufacturing of a wide range of products from engine components to medical implants. While finite element modeling and closed-loop control have been identified key for predicting and engineering part qualities in PBF, existing results in each realm are developed in opposite computational architectures wildly different in time scale. This paper builds a first-instance closed-loop simulation framework by integrating high-fidelity finite element modeling with feedback controls originally developed for general mechatronics systems. By utilizing the output signals (e.g., melt pool width) retrieved from the finite element model (FEM) to update directly the control signals (e.g., laser power) sent to the model, the proposed closed-loop framework enables testing the limits of advanced controls in PBF and surveying the parameter space fully to generate more predictable part qualities. Along the course of formulating the framework, we verify the FEM by comparing its results with experimental and analytical solutions and then use the FEM to understand the melt-pool evolution induced by the in- and cross-layer thermomechanical interactions. From there, we build a repetitive control (RC) algorithm to attenuate variations of the melt pool width. 

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3. Distributed Temperature Control in Laser-Based Manufacturing

   https://doi.org/10.1115/1.4046154  

   Zheng, Chengjian; Wen, John T.; Diagne, Mamadou (June 2020, Journal of Dynamic Systems, Measurement, and Control)

   Abstract Temperature control is essential for regulating material properties in laser-based manufacturing. Motion and power of the scanning laser affect local temperature evolution, which in turn determines the a posteriori microstructure. This paper addresses the problem of adjusting the laser speed and power to achieve the desired values of key process parameters: cooling rate and melt pool size. The dynamics of a scanning laser system is modeled by a one-dimensional (1D) heat conduction equation, with laser power as the heat input and heat dissipation to the ambient. Since the model is 1D, length and size are essentially the same. We pose the problem as a regulation problem in the (moving) laser frame. The first step is to obtain the steady-state temperature distribution and the corresponding input based on the desired cooling rate and melt pool size. The controller adjusts the input around the steady-state feedforward based on the deviation of the measured temperature field from the steady-state distribution. We show that with suitably defined outputs, the system is strictly passive from the laser motion and power. To avoid over-reliance on the model, the steady-state laser speed and power are adaptively updated, resulting in an integral-like update law for the feedforward. Moreover, the heat transfer coefficient to the ambient may be uncertain, and can also be adaptively updated. The final form of the control law combines passive error temperature field feedback with adaptive feedforward and parameter estimation. The closed-loop asymptotical stability is shown using the Lyapunov arguments, and the controller performance is demonstrated in a simulation. 

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4. Understanding Melt Pool Behavior of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing

   https://doi.org/10.3390/MI15020170  

   Zhang, Zilong; Zhang, Tianyu; Sun, Can; Karna, Sivaji; Yuan, Lang (February 2024, Micromachines)

   In the laser powder bed fusion additive manufacturing process, the quality of fabrications is intricately tied to the laser–matter interaction, specifically the formation of the melt pool. This study experimentally examined the intricacies of melt pool characteristics and surface topography across diverse laser powers and speeds via single-track laser scanning on a bare plate and powder bed for 316L stainless steel. The results reveal that the presence of a powder layer amplifies melt pool instability and worsens irregularities due to increased laser absorption and the introduction of uneven mass from the powder. To provide a comprehensive understanding of melt pool dynamics, a high-fidelity computational model encompassing fluid dynamics, heat transfer, vaporization, and solidification was developed. It was validated against the measured melt pool dimensions and morphology, effectively predicting conduction and keyholing modes with irregular surface features. Particularly, the model explained the forming mechanisms of a defective morphology, termed swell-undercut, at high power and speed conditions, detailing the roles of recoil pressure and liquid refilling. As an application, multiple-track simulations replicate the surface features on cubic samples under two distinct process conditions, showcasing the potential of the laser–matter interaction model for process optimization. 

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5. Control-Oriented Modeling and Repetitive Control in In-Layer and Cross-Layer Thermal Interactions in Selective Laser Sintering

   https://doi.org/10.1115/1.4046367  

   Wang, Dan; Jiang, Tianyu; Chen, Xu (January 2021, ASME Letters in Dynamic Systems and Control)

   null (Ed.)

   Abstract Although laser-based additive manufacturing (AM) has enabled unprecedented fabrication of complex parts directly from digital models, broader adoption of the technology remains challenged by insufficient reliability and in-process variations. In pursuit of assuring quality in the selective laser sintering (SLS) AM, this paper builds a modeling and control framework of the key thermodynamic interactions between the laser source and the materials to be processed. First, we develop a three-dimensional finite element simulation to understand the important features of the melt pool evolution for designing sensing and feedback algorithms. We explore how the temperature field is affected by hatch spacing and thermal properties that are temperature-dependent. Based on high-performance computer simulation and experimentation, we then validate the existence and effect of periodic disturbances induced by the repetitive in- and cross-layer thermomechanical interactions. From there, we identify the system model from the laser power to the melt pool width and build a repetitive control algorithm to greatly attenuate variations of the melt pool geometry. 

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