Spatiotemporal Projection‐Based Additive Manufacturing: A Data‐Driven Image Planning Method for Subpixel Shifting in a Split Second

Abstract

Additive manufacturing (AM) is a digital manufacturing process that can directly convert a computer‐aided design model into a physical object in a layer‐by‐layer manner. Due to the additive and discrete nature of the digital manufacturing process, AM needs to find a trade‐off between process resolution and production efficiency. Traditional AM processes balance the resolution and efficiency by tuning the processes either in the temporal domain (e.g., higher speed in serial processes) or in the spatial domain (e.g., more tools in parallel processes). To improve the resolution without sacrificing efficiency, a data‐driven mask image planning method based on subpixel shifting in a split second by tuning the process in both temporal and spatial domains is presented. The method is based on the optimized pixel blending principle and a fast error diffusion‐based optimization model. Various simulation and experimental tests are carried out to verify the developed subpixel shifting method. The experimental results demonstrate the data‐driven‐based mask image calibration and planning techniques significantly improve the fabricated part quality without compromising the process efficiency. The presented spatiotemporal strategy may shed light for future research on the projection‐based AM processes.

Continuous Vat Photopolymerization for Optical Lens Fabrication

“…A light cone within the spherical angle Ω derived from integrating the acceptance angle over the from [0, 2𝜋], is the light collected by the objective lens (Figure 3a). [40] Assume all light collected by the objective lens will be projected to the building platform. The light intensity on the building platform is given by:…”

Vibration-assisted vat photopolymerization for pixelated-aliasing-free surface fabrication

“…Guided by the LCD light intensity simulation, a vibrationassisted MIP-VPP system is presented to generate a more uniform light intensity of an LCD mask image and eliminate pixelated aliasing. From the previous work for the DMD-based MIP-VPP systems [28,30], we observed that a mask image's shape and light intensity can be tuned by dividing the oneshot UV exposure into multiple exposures, each with a slight shift in the XY directions. Inspired by this, we deduced the The schema of the vibration-assisted MIP-VPP process is illustrated in figure 3(a).…”

“…The simulation displays the light intensity of five consecutive pixels to represent the light intensity across the entire mask image. The relative light intensity of each single pixel is depicted in red, and the convoluted relatively light intensity is shown by a black line [28,30]. The solid red line represents the original position of the light intensity in the LCD mask image without vibration, and the dashed line denotes the shifted mask image positions during vibration.…”

Hopping Light Vat Photopolymerization for Multiscale Fabrication

“…The second category of methods [30,31] utilizes the pixel blending principle to improve the resolution without sacrificing production efficiency. Unlike static projection, the fabrication of each layer is accomplished by projecting n 2 mask images with subpixel size-shifting (p/n, p is the nominal pixel size of the projector) between each projection.…”