Browsing by Subject "Dynamic optimization"

Now showing 1 - 4 of 4

Open Access
Improving the dimensional accuracy of micro parts 3D printed with projection-based continuous vat photopolymerization using a model-based grayscale optimization method
(Elsevier, 2022-09) Guven, Ege; Karpat, Yigit; Cakmakci, Melih
Micro-scale additive manufacturing has seen significant growth over the past years, where improving the accuracy of complex micro-scale geometries is seen as an important challenge. Using grayscale images rather than black and white images during production is an effective method to improve the fabrication quality. This paper presents a model-based optimization method for improving the dimensional accuracy of parts using voxel-based grayscale dynamic optimization during continuous 3D printing. A detailed solidification model has been developed and used to estimate the curing dynamics of the resin used in 3D printing. The irradiance of the light beam projected for each pixel influences a larger volume on the resin than the targeted voxel. The proposed model-based method optimizes the images considering the light distribution from all closely related pixels to maintain the accuracy of the micro part. The results of this method have been applied to the printing of a complex 3D part to show that optimized grayscale images improve the areas with overcuring significantly. It is shown that the number of overcured voxels was reduced by 24.7% compared to the original images. Actual printing results from our experimental setup confirm the improvements in the accuracy and precision of the printing method.
Open Access
Learning by imitation
(Elsevier BV, 1999) Başçı, E.
This paper introduces a learning algorithm that allows for imitation in recursive dynamic games. The Kiyotaki-Wright model of money is a well-known example of such decision environments. In this context, learning by experience has been studied before. Here, we introduce imitation as an additional channel for learning. In numerical simulations, we observe that the presence of imitation either speeds up social convergence to the theoretical Markov-Nash equilibrium or leads every agent of the same type to the same mode of suboptimal behavior. We observe an increase in the probability of convergence to equilibrium, as the incentives for optimal play become more pronounced.
Open Access
Model-based optimization of microscale parts printed with projection-based continuous vat photopolymerization
(2022-08) Güven, Ege
Micro-scale additive manufacturing has seen significant growth over the past years, where improving the accuracy of complex micro-scale geometries is seen as an important challenge. Using grayscale images rather than black and white images during production is an effective method to improve the fabrication quality. This thesis presents a model-based optimization method for improving the dimensional accuracy of parts using voxel-based grayscale dynamic optimization during continuous 3D printing. A detailed solidification model has been developed and used to estimate the curing dynamics of the resin used in 3D printing. The irradiance of the light beam projected for each pixel influences a larger volume on the resin than the targeted voxel. The proposed model-based method optimizes the images considering the light distribution from all closely related pixels to maintain the accuracy of the micro part. The results of this method have been applied to the printing of complex 3D parts to show that optimized grayscale images improve the areas with overcuring significantly. It is shown that the number of overcured voxels was reduced by 24.7% compared to the original images. Actual printing results from the experimental setup confirm the improve-ments in the accuracy and precision of the printing method. The optimization method has been further improved by allowing variable printing speed during pro-duction and optimizing the speed profile of the print alongside grayscaling. This approach allows for printing of certain geometries that would otherwise be challenging to produce accurately. Computational limitations of performing speed and grayscale optimization simultaneously has been overcome by utilizing the symmetry of certain special cases to reduce optimization variables.
Open Access
Productivity enhancement in top-down VPP via concurrent grayscaling and platform speed profile optimization for symmetrical parts having micro scale features
(Springer, 2024-06-14) Güven, Ege; Karpat, Yiğit; Çakmakcı, Melih
Vat Photopolymerization (VPP), a widely adopted additive manufacturing technique, has revolutionized the domain of 3D printing by enabling the precise fabrication of complex structures, including intricate details. However, challenges remain in achieving optimal print quality while improving speed. Conventionally, grayscaling has been used to improve part accuracy in continuous VPP systems as the build platform speed remains constant. Considering a detailed photocurable resin solidification model, together with grayscaling, this study aims to improve productivity by optimizing platform speed profile while maintaining the build quality. While the optimization formulation presented here can be applied to any part, the computational limitations due to the employment of a voxel-based approach and the nonlinear nature of the resulting optimization problem are simplified by adopting a novel discretization methodology utilizing the symmetric properties of the target 3D part. By employing ring elements instead of voxels for cylindrical symmetrical parts, the computational load of the optimization algorithm is dramatically reduced. Experimental results show the proposed concurrent optimization reduces print time by 56% while maintaining superior print surface quality on an hourglass-shaped test part having micro scale features.