Manufacturability analysis for additive manufacturing using a novel feature recognition technique

ABSTRACTAdditive Manufacturing (AM) increases much design freedom for designers to conceive complex parts. However, the increased complexity makes the manufacturability analysis difficult for the designed parts when applying traditional methods. To solve this problem, this paper introduces a new feature-based method for manufacturability analysis in AM by using Heat Kernel Signature. This method can both identify geometric features and manufacturing constrains which are defined in this paper for comprehensive analysis from the perspective of manufacturing to support the redesign and downstream process planning. A couple of example part models including a standard testing part for AM are used to demonstrate the feasibility of applying the proposed method for feature recognition and manufacturability analysis.

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