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Intelligent Process Planning for Additive Manufacturing

机译:添加剂制造的智能流程规划

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This paper introduces an intelligent approach for process planning of additive manufacturing (AM) in digital environment. A global adaptive slicing algorithm is developed and embedded in the introduced concept, which determines the layer thicknesses and widths based on the minimization of the deviations between the CAD model boundary and its stepped approximation. It is discussed that there are different metrics to measure the deviations such as cusp height, cusp volume and surface roughness criteria. A new criterion is developed to globally minimize the overall volumetric deviations of the final product from the desired geometric model. The proposed methodology uses the locally optimized layer thicknesses as the inputs to calculate the globally optimized layer thicknesses and the optimal contour for each layer. The global optimization problem is highly nonlinear that can be solved with a metaheuristic algorithm such as Simulated Annealing.
机译:本文介绍了一种智能方法,用于数字环境中添加剂制造的过程规划。在引入的概念中开发并嵌入了全局自适应切片算法,其基于最小化CAD模型边界和其阶梯式近似的偏差来确定层厚度和宽度。讨论了,有不同的度量来测量诸如CUSP高度,CUSP体积和表面粗糙度标准的偏差。开发了一种新标准,以全局最小化最终产品与所需几何模型的总体体积偏差。所提出的方法使用本地优化的层厚度作为输入来计算全局优化的层厚度和每层的最佳轮廓。全局优化问题是高度非线性,可以用诸如模拟退火的成群质算法来解决。

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