Abstract
This paper discusses a set of geometry based computational pre-processing algorithms developed for Powder Bed Fusion Additive Manufacturing (PBFAM) processes. To start with, based on an initial part design, an automatic support structure generation module generates customized CAD-based support structures for a given part build orientation. Various additive manufacturing (AM) parameters and Design for Additive Manufacturing (DFAM) metrics are calculated on the fly for assigning producibility scores at different part build orientations. A set of stand-alone computational geometry-based algorithms with associated graphical user interfaces (GUI) are developed for calculating support structure parameters, as well as for detecting and highlighting DFAM features that are difficult to manufacture. These stand-alone tools provide a quantified output for each of the parameters or features, which are then used downstream during the producibility index (PI) calculation. An algorithm that evaluates ease of removing supports during the post-processing phase, and suggests the optimum number of setups needed to remove support structures is developed. Finally, Producibility Index, which is a weighted optimization metric, brings together the quantified outputs of the DFAM analysis, support structure parameters, accessibility analysis and suggests the best build orientations for the given part geometry. All the algorithms are implemented within the Siemens NX modelling environment utilizing C++ and NX API functions. The developed algorithm and tools have been succesfully demonstrated on two sample parts.
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