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.
Highlights
Additive Manufacturing (AM), derived from Rapid Prototyping (RP), has been investigated and developed for more than three decades
Several nesting algorithms are present in the literature, many of which are based on optimization algorithms that often require different iterations to obtain the final configuration
The technical specifications definition for the previsional model implementation, has led the need to develop a nesting algorithm for the computation of the printable components number on a given printing plan
Summary
Additive Manufacturing (AM), derived from Rapid Prototyping (RP), has been investigated and developed for more than three decades. The characteristics of AM processes, the features of part group, the production contexts of AM service bureaus and the specific preferences and requirements of users should be taken into consideration when doing the multi- parts placement These factors form the customized constraints of AM to make this problem a special variant of classical nesting or packing problem. In this paper a new algorithm for 3D printing nesting has presented and it has been developed within the definition of a previsional model that aims to evaluate the performance to manufacture a particular component comparing different available 3D printing technologies For this reason, the main purpose of this innovative algorithm is providing to previsional model a worth solution to compute a possible nesting configuration for a given platform. The objective was, to obtain an effective tool able to compute a possible nesting configuration (number of components that it is possible to print with a given 3D printing technology and with a single job) to feed the previsional model in order to compute several KPI that allow to evaluate the available technologies in terms of cost estimation and technological compatibility
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