Preliminary communication

https://doi.org/10.17559/TV-20170506140109

Application of Linear Optimization on Parameters of 3D FDM Print

Oskar Zemcik orcid.org/0000-0001-7786-3531 ; Brno University of Technology, Faculty of Mechanical Engineering, Institute of Manufacturing Technology, Technická 2896/2, 616 69 Brno, Czech Republic
Josef Sedlak orcid.org/0000-0002-9819-8259 ; Brno University of Technology, Faculty of Mechanical Engineering, Institute of Manufacturing Technology, Technická 2896/2, 616 69 Brno, Czech Republic

Abstract

Nowadays, a fused deposition modelling (also called "FDM") belongs to one of the most widespread additive methods of 3D print. It allows producing both models for functional verification or casts and functional components. The main advantage of this technology is an option to produce complex components of a difficult shape independent of their outer and inner surfaces. Moreover, this mentioned technology brings the decreasing of production costs in comparison with the other well-known additive methods. The final quality of a product depends on the used material and on technological conditions at the same time. The number of parameters and limits of the complete printing process is enormous. The choice of the individual parameters by a trial-and-error procedure is very time-consuming. Therefore, a use of linear optimization for finding of optimal values of chosen print parameters can be offered. For forming of the required procedures, it seems to be necessary to choose structural variables, find an appropriate objective function and deduce properly limiting conditions in a linear shape, which relates to a linear measurement. The final solution enables, on the basis of the selected initial conditions, to choose optimal parameters of the 3D print for a given material and production equipment in a relatively short period.

Keywords

3D Print; FDM; Fused Deposition Modelling; linear programming; minimal costs; optimization

Hrčak ID:

223339

URI

https://hrcak.srce.hr/223339

Publication date:

25.7.2019.

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