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Efficient slicing for layered manufacturing
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AI
DOI：10.1108/13552549810239003.png)
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摘要
En 中文
An adaptive slicing algorithm that can vary the layer thickness in relation to local geometry is presented. The algorithm is based on three fundamental concepts: choice of criterion for accommodating complexities of surfaces, recognition of key characteristics and features of the object, and development of a grouping methodology for facets used to represent the object. Four criteria, cusp height, maximum deviation, chord length and volumetric error per unit length, are identified and the layer thickness is adjusted such that one of the four is met. Next, key characteristics of the object, such as horizontal and vertical surfaces, pointed edges and ends, are identified based on the local changes in surface complexity, and slice based feature recognition is introduced to identify the nature of a feature, protrusion or depression, by studying the slice data. Note that the present approach uses information only from the tessellated model, and thus is different from current implementations. Finally, the concept of grouping of the facets based on their vertex coordinates is developed to minimize the number of searches for possible intersection of the facets with a slice plane. The slicing algorithm is interfaced with adaptive laminated machining and the stereolithography process through a CNC post processor and a hatching algorithm respectively. A comparison of the estimated surface quality and build time indicates that adaptive slicing produces superior parts in a shorter build time. The implementation of this work is protected under US Patent laws (Patent # 5,596,504, January 1997).
期刊
IF:
3.6
论文数:
2.2K
被引数:
7.7K
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