Significant savings in cost and time can be achieved in additive processes by manufacturing multiple parts in a single setup to obtain efficient machine volume utilization. In this paper, the authors have developed a previsional model able to evaluate the potential performance of various printing technologies for the execution of a given job. This model aims to support technicians in choosing the best solution starting from a specific machine architecture and printing volume. In particular, the model is able to evaluate, from a qualitative and quantitative point of view, the performance of each technology in a transversal manner, taking into consideration the aspects connected to printing: costs, time, and technological parameters. Within the core of the previsional model, there are multiple algorithms able to compute different key performance indicators (nine KPIs). For the computation of some of them, it was necessary to quantitatively evaluate aspects related to nesting operations or to the arrangement of several components within the printing base depending on the dimensional characteristics of the component, the printing direction, and its dimensional and geometric characteristics (rectangular or circular). Starting from this need, the developed nesting algorithm has given a specific answer.
Nesting algorithm for optimization part placement in additive manufacturing
Primo, T;Del Prete, A;
2022-01-01
Abstract
Significant savings in cost and time can be achieved in additive processes by manufacturing multiple parts in a single setup to obtain efficient machine volume utilization. In this paper, the authors have developed a previsional model able to evaluate the potential performance of various printing technologies for the execution of a given job. This model aims to support technicians in choosing the best solution starting from a specific machine architecture and printing volume. In particular, the model is able to evaluate, from a qualitative and quantitative point of view, the performance of each technology in a transversal manner, taking into consideration the aspects connected to printing: costs, time, and technological parameters. Within the core of the previsional model, there are multiple algorithms able to compute different key performance indicators (nine KPIs). For the computation of some of them, it was necessary to quantitatively evaluate aspects related to nesting operations or to the arrangement of several components within the printing base depending on the dimensional characteristics of the component, the printing direction, and its dimensional and geometric characteristics (rectangular or circular). Starting from this need, the developed nesting algorithm has given a specific answer.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
