Topology optimization for precision additive manufacturing
Rajit Ranjan (PhD candidate), Can Ayas (supervisor) and Matthijs Langelaar (supervisor)
This project is a part of initiative by EU Framework Program for Research and Innovation-Horizon 2020, titled as Precision Additive Metal Manufacturing, PAM2. The overall aim of this project is to investigate complete AM process chain and ensure the availability of high precision in AM processes and (computational) design procedures. For this purpose, the PAM2 consortium, which constitutes of 4 industrial and 6 academic partners, is addressing each aspect related to the AM process. Among these, TU Delft focuses on the ‘design for AM’ aspect for developing advance computational design techniques.
Development of new topology optimization techniques which can be applied to realistic precision components. These techniques integrate additive manufacturing constraints and reduced-order process modelling. The latter are required for prediction of process-induced stresses, product distortion and changes in material properties.
To fully exploit the advantages of AM’s associated design freedom, topology optimization is often used to generate an optimal design for an AM part. Current topology optimization tools however do not take into account that local overheating during AM processing might occur. This overheating can result in microstructural inhomogeneity, defect formation, poor surface finish and undesired deformation and/or mechanical properties for the final AM part. Within the design work package of PAM2, a computationally inexpensive simplified thermal model, called a ‘hotspot detector’, is developed to detect zones of local heat concentration. Finite element implementation of the hotspot detector is integrated with the density based topology optimization in order to generate robust AM designs that are expected to be free of local overheating zones. An important advantage of this physics based method over already existing geometry based approaches is that it incorporates the temperature response of a geometry instead of imposing explicit prohibition of overhangs. The latter is found to be occasionally over restrictive, leading to sub optimal designs while in some cases it is insufficient for constraining local overheating
The hotspot based TO is implemented on an industrial test case where the design of a mould insert is optimized. The mould insert, which is to be manufactured using powder bed fusion of Maraging steel 300, is optimized for reduction in mass and production time. The loading condition mimicked the injection pressure load on the runners and mould cavities using the maximum possible pressure multiplied by a safety factor of 1.5. The optimised designs using both standard and hotspot TO are shown. Due to symmetry, the presented results are for half of the mould. The mass has been reduced to 50% of the initial design, while the production time is reduced by 43%. Lastly, the hotspot temperatures were found to be 30% lower in the design found using hotspot TO, compared to that of standard TO. This is primarily achieved by avoiding the overhanging features present in the standard TO case which, if fabricated, would cause significant dross leading to rough surfaces and loss of precision.
- Ranjan, R., Yang, Y., Ayas, C., Langelaar, M. and Van Keulen, F. (2017). Controlling Local Overheating in Topology Optimization for Additive Manufacturing. Special Interest group Additive Manufacturing Euspen conference, Belgium
- Ranjan, R., Ayas, C., Langelaar, M. and Van Keulen, F. (2018). Towards design for precision additive manufacturing: A simplified approach for detecting heat accumulation. ASPE and Euspen Summer Topical Meeting, Berkeley, USA
- Ranjan, R., Ayas, C., Langelaar, M. and Van Keulen, F. (2019). Detecting Overheating in AM Parts using Computationally Efficient Thermal Models. SIM-AM conference, Pavia, Italy
- Sinico, M., Ranjan, R., Moshiri, M., Ayas, C., Langelaar, M., Witvrouw, A., Van Keulen, F. and Dewulf, W. (2019) A mold insert case study on Topology Optimized design for Additive Manufacturing. Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, Austin (TX), USA