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While predicting shape deviation belongs to the forward problem, minimizing shape deviation of AM-built products is a challenging inverse problem due to geometric complexity, product varieties, material phase changing and shrinkage, interlayer bonding, and limited sample data. Various methods and strategies have been developed to improve geometric quality of AM processes. We summarize the related work in Table 6.1 with a sample literature given for each category.

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Foundation of Offline Optimal Compensation of 3D Shape Deviation

  • 章节

  • 发表日期：

    2025年

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  • Qiang Huang

摘要

While predicting shape deviation belongs to the forward problem, minimizing shape deviation of AM-built products is a challenging inverse problem due to geometric complexity, product varieties, material phase changing and shrinkage, interlayer bonding, and limited sample data. Various methods and strategies have been developed to improve geometric quality of AM processes. We summarize the related work in Table 6.1 with a sample literature given for each category.