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NUMERICAL SIMULATION .1 Part orientation

An efficient approach based on geometrical analysis to optimize AM process

4 NUMERICAL SIMULATION .1 Part orientation

In order to demonstrate the effectiveness of the described approach about the definition of the optimal orientation, numerical simulation results of a selected case study are presented in this paragraph. Two different kinds of orientation are assumed for the component characterized respectively by not optimised orientation and orientation for minimum distortion.

For each orientation of the component, an Additive Manufacturing Simulation was carried out by means of the software Simufact™ Additive by MSC® Software. In the frame of the powder bed fusion (PBF) methods, the additive manufacturing process optimization faces two main issues affecting the metal-based manufacturing processes: the distortion of the geometry and the residual stresses. The first undesired effect could cause deviations from the optimal shape and require the use of outside tolerances. The second issue, instead, could be reason for cracking, failure of supports and reduction in the strength and fatigue life of the component.

The macro scale approach followed by Simufact™ Additive makes use of a voxel technique that discretizes the entire volume in millions of finite elements and adopts a layer-based additive manufacturing process. The distortion effect is a direct consequence of the heat distribution on the component that causes a not homogeneous thermal expansion depending on the local temperature of the metal. This phenomenon in Simufact™ Additive is predicted by the

“inherent strain method”. This method is beneficial due to the faster computation time in comparison with coupled thermo-mechanical simulations. The inherent strain method assumes that the laser spot size is negligible compared to the built components. The inherent strains must be determined preliminarily and are then used to calculate the residual stress and distortions by imposing them on linear elastic purely mechanical FE models.

4.2 Simulation parameters and results

In this paragraph, a series of simulation parameters set before running the simulation are reported. The machine type adopted for the layer-based process is M400 manufactured by EOS.

The part to produce, whose model has been implemented by means of a STL file, is made of AlSi10Mg, has a relative material density equal to 99%, a surface of 79.369 mm2 and a volume of 319.543 mm3. The supports, automatically created in Additive Simufact™ environment, have relative material density equal to 80%, isotropic elastic properties and isotropic thermal conductivity. A base plate is defined with the same material of the part and the supports and with dimensions: 400x400x10 mm3.

As a result of the simulations, it was possible to demonstrate a reduction of deviations from nominal geometry, with the orientation suggested by AMTOP® for minimum distortion compared to not optimised configuration, from -4.01 ÷ 3.88 mm to -2.14 ÷ 2.90 mm (Figure 5

& Figure 6).

F. Valente & S. Papadopoli

Figure 5: Surface deviation [mm] for the component with not optimised orientation (case A)

Figure 6: Surface deviation [mm] for the component oriented with minimum distortion (case B)

5 CONCLUSIONS

The described activity relates to the programming of a software interface for setting user parameters and individual jobs. The software provides detailed information on the laser path and physical variables, which can be used for off-line or in-line monitoring and control. It is also possible to view the entire laser path and the detail of each individual trait, and to generate a file containing structured data as a FEM model, for setting boundary conditions and process parameters for the definition of a process simulation model.

One of the possible part orientations provided by AMTOP® (for minimum distortion) and the configuration with not optimised orientation were analysed with FE macro-scale simulation.

The numerical results of each calculation were compared in terms of surface deviation of the original shape computed after the supports removal and cooling.

F. Valente & S. Papadopoli

As expected, the orientation of the component for minimum distortion allows to reduce the final part surface deviation range. This effect is assumed to be related to a more homogeneous distribution of the temperature on the volume that determines a more regular thermal expansion of the material.

ACKNOWLEDGEMENTS

The work has been partially funded through the participation to the innovation project

“STAMP” (Sviluppo Tecnologico dell'Additive Manufacturing in Piemonte), within the program agreement MIUR - Piemonte Region, action 3 of "Smart Factory". The authors are grateful to all the partners who were committed in the task: 3D-NT, Prima Electro, FCA, GE AVIO, ELLENA, APR and to the project leader Prima Industrie.

REFERENCES

[1] A. Henrot and M. Pierre, Shape Variation and Optimization: A Geometrical Analysis, European Mathematical Society, (April 25, 2018).

[2] J. W. Booth, J. Alperovich, T. N. Reid, K. Ramani, The Design for Additive Manufacturing Worksheet., Proceedings of the ASME 2016 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2016, August 21-24, 2016, Charlotte, North Carolina, USA.

[3] Zeng, Kai, Optimization of support structures for selective laser melting. (2015). Electronic Theses and Dissertations. Paper 2221. http://dx.doi.org/10.18297/etd/2221

[4] Cherkaev, Andrej & Cherkaev, Elena. (2002). Structural Optimization and Biological “Designs”.

10.1007/0-306-46939-1_22.

[5] Feppon, Florian & Michailidis, Georgios & Sidebottom, Mark & Allaire, Grégoire & Krick, Brandon & Vermaak, Natasha. (2016). Introducing a level-set based shape and topology optimization method for the wear of composite materials with geometric constraints. Structural and Multidisciplinary Optimization. 10.1007/s00158-016-1512-4.

[6] Pinar Mert Cuce, Erdem Cuce, Optimization of configurations to enhance heat transfer from a longitudinal fin exposed to natural convection and radiation, International Journal of Low-Carbon Technologies, Volume 9, Issue 4, December 2014, Pages 305–310, https://doi.org/10.1093/ijlct/ctt005.

[7] Malekipour, Ehsan & Tovar, Andres & El-Mounayri, Hazim. (2018). Heat Conduction and Geometry Topology Optimization of Support Structure in Laser-Based Additive Manufacturing.

10.1007/978-3-319-62834-9_4.

[8] Wang, Cunfu & Qian, Xiaoping & Gerstler, William & Shubrooks, Jeff. (2019). Boundary Slope Control in Topology Optimization for Additive Manufacturing: for Self-support and Surface Roughness *. Journal of Manufacturing Science and Engineering. 10.1115/1.4043978.

[9] Taufik, Mohammad & Jain, Prashant. (2014). Role of build orientation in layered manufacturing:

A review. International Journal of Manufacturing Technology and Management. 27. pp.47 - 73.

10.1504/IJMTM.2013.058637.

[10] Peng, H.; Ghasri-Khouzani, M.; Gong, S.; Attardo, R.; Ostiguy, P; Aboud Gatrell, B.; Budzinski,

F. Valente & S. Papadopoli

J.; Tomonto, C.; Neidig, J; Shankar, M.R.; Billo, R.; Go, D.B.; Hoelzle, D.: Optimization of build orientation for minimum thermal distortion in DMLS metallic Additive Manufacturing, Solid Freeform Fabrication: Proceedings of the 28th Annual International Solid Freeform Fabrication Symposium, 2017.

[11] E. Ulu, E. Korkmaz, K. Yay, O. Burak Ozdoganlar, L. Burak Kara, Enhancing the Structural Performance of Additively Manufactured Objects Through Build Orientation Optimization, J.

Mech. Des. 137 (2015) 111713. doi:10.1115/1.4030998.

[12] C. Thompson, David & Crawford, Richard. (1998). Optimizing Part Quality with Orientation.

[13] Das, Paramita & Chandran, Ramya & Samant, Rutuja & Anand, Sam. (2015). Optimum Part Build Orientation in Additive Manufacturing for Minimizing Part Errors and Support Structures.

Procedia Manufacturing. 1. 343-354. 10.1016/j.promfg.2015.09.041.

[14] Ninshu Ma, Keiji Nakacho, Takahiko Ohta, Naoki Ogawa, Akira Maekawa, Hui Huang, and Hidekazu Murakawa. Inherent strain method for residual stress measurement and welding distortion prediction. In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering, pages V009T13A001–V009T13A001. American Society of Mechanical Engineers, 2016.

[15] ] MSC Simufact. Simufact additive tutorial, April 2018.

[16] ISO/ASTM 52915:2016, Specification for additive manufacturing file format (amf) version 1.2 [17] "ISO/IEC 23271, Common Language Infrastructure". ISO. Retrieved September 27, 2006.