Abstract Industries such as orthodontics and athletic apparel are adopting vat photopolymerization (VP) to manufacture customized products with performance tailored through geometry. However, vat photopolymerization is limited by low manufacturing speeds and the trade-off between manufacturable part size and feature resolution. Current VP platforms and their optical sub-systems allow for simultaneous maximization of only two of three critical manufacturing metrics: layer fabrication time, fabrication area, and printed feature resolution. The Scanning Mask Projection Vat Photopolymerization (S-MPVP 1 ) system was developed to address this shortcoming. However, models developed to determine S-MPVP process parameters are accurate only for systems with an intensity distribution that can be approximated with a first order Gaussian distribution. Limitations of optical elements and the use of heterogeneous photopolymers result in non-analytic intensity distributions. Modeling the effect of non-analytic intensity distribution on the resultant cure profile is necessary for accurate manufacturing of multiscale products. In this work, a model to predict the shape of cured features using analytic and non-analytic intensity distribution is presented. First, existing modeling techniques developed for laser and mask projection VP processes were leveraged to create a numerical model to relate the process parameters (i.e. scan speed, mask pattern irradiance) of the S-MPVP system with the resulting cure profile. Then, by extracting the actual intensity distribution from the resin surface, we demonstrate the model's ability to use non-analytic intensity distribution for computing the irradiance for any projected pattern. Using a custom S-MPVP system, process parameters required to fabricate test specimens were experimentally determined. These parameters were then input into the S-MPVP model and the resulting cure profiles were simulated. Comparison between the simulated and printed specimens dimensions demonstrates the model’s effectiveness in predicting the dimensions of the cured shape with an error of 2.9%.

中文翻译：

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用于多尺度增材制造的扫描掩模投影缸光聚合系统建模

摘要 正畸和运动服装等行业正在采用还原光聚合 (VP) 来制造具有通过几何形状定制的性能的定制产品。然而，还原光聚合受到低制造速度和可制造零件尺寸和特征分辨率之间的权衡的限制。当前的 VP 平台及其光学子系统只允许同时最大化三个关键制造指标中的两个：层制造时间、制造面积和印刷特征分辨率。开发了扫描掩模投影缸光聚合 (S-MPVP 1 ) 系统来解决这个缺点。然而，为确定 S-MPVP 工艺参数而开发的模型仅适用于强度分布可以近似为一阶高斯分布的系统。光学元件的局限性和异质光聚合物的使用导致非解析强度分布。模拟非解析强度分布对所得固化曲线的影响对于精确制造多尺度产品是必要的。在这项工作中，提出了一种使用解析和非解析强度分布来预测固化特征形状的模型。首先，利用为激光和掩模投影 VP 工艺开发的现有建模技术来创建数值模型，以将 S-MPVP 系统的工艺参数（即扫描速度、掩模图案辐照度）与所得固化曲线相关联。然后，通过从树脂表面提取实际的强度分布，我们展示了模型' s 使用非解析强度分布计算任何投影图案的辐照度的能力。使用定制的 S-MPVP 系统，通过实验确定制造试样所需的工艺参数。然后将这些参数输入到 S-MPVP 模型中，并模拟得到的固化曲线。模拟和打印样本尺寸之间的比较表明该模型在预测固化形状尺寸方面的有效性，误差为 2.9%。