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One of the main decision points for selecting a 3DP technology for production applications is the cost

per produced part. In order to enable this choice-point it is required to provide a relatively accurate

estimation of the cost per part. We have developed a way to calculate the cost automatically,

transparently to the user and more accurately than most of the currently available solutions for the

different 3DP technologies, by using a trained machine learning model in the nesting algorithm

executed in the Pre-print SW application. Then, the proposed method is intended to be combined with

any other packing algorithm which may have any optimization target. The packing algorithm generates

job nesting configurations and our proposed method analyzes if the solution found meets the cost

requirement previously defined by the user. If the solution meets the cost requirement it is accepted. In

any other case the solution is rejected, and the packing algorithm is re-executed to find a different


Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.