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1. 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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2. New Hammerstein Modeling and Analysis for Controlling Melt Pool Width in Powder Bed Fusion Additive Manufacturing

   https://doi.org/10.1115/1.4050079  

   Wang, Dan ; Zhao, Xinyu ; Chen, Xu ( July 2021 , ASME Letters in Dynamic Systems and Control)

   null (Ed.)

   Abstract Despite the advantages and emerging applications, broader adoption of powder bed fusion (PBF) additive manufacturing is challenged by insufficient reliability and in-process variations. Finite element modeling and control-oriented modeling have been shown to be effective for predicting and engineering part qualities in PBF. This paper first builds a finite element model (FEM) of the thermal fields to look into the convoluted thermal interactions during the PBF process. Using the FEM data, we identify a novel surrogate system model from the laser power to the melt pool width. Linking a linear model with a memoryless nonlinear submodel, we develop a physics-based Hammerstein model that captures the complex spatiotemporal thermomechanical dynamics. We verify the accuracy of the Hammerstein model using the FEM and prove that the linearized model is only a representation of the Hammerstein model around the equilibrium point. Along the way, we conduct the stability and robustness analyses and formalize the Hammerstein model to facilitate the subsequent control designs. 

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3. 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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4. 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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5. ‘Seeing’ the Temperature Inside the Part during the Powder Bed Fusion Process

   Wood, N. ; Hoelzle, D. ( August 2019 , Proceedings of the 2019 Annual International Solid Freeform Fabrication Symposium)

   Powder Bed Fusion (PBF) is a type of Additive Manufacturing (AM) technology that builds parts in a layer-by-layer fashion out of a bed of metal powder via the selective melting action of a laser or electron beam heat source. The technology has become widespread, however the demand is growing for closed loop process monitoring and control in PBF systems to replace the open loop architectures that exist today. This paper demonstrates the simulated efficacy of applying closed-loop state estimation to the problem of monitoring temperature fields within parts during the PBF build process. A simplified LTI model of PBF thermal physics with the properties of stability, controllability and observability is presented. An Ensemble Kalman Filter is applied to the model. The accuracy of this filters’ predictions are assessed in simulation studies of the temperature evolution of various test parts when subjected to simulated laser heat input. The significant result of this study is that the filter supplied predictions that were about 2.5x more accurate than the open loop model in these simulation studies. 

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