Advanced process optimization

We combine advanced industrial process characterization and computational modeling techniques to optimize industrial manufacturing processes.

Advanced Industrial Process Characterization

For more details, please refer to my publications:

Advanced process characterization of an industrial low pressure die casting process for wheel production (open access)

https://www.mdpi.com/2075-4701/10/5/563

Advanced process characterization of an industrial counter pressure casting process for automotive suspension parts

Advanced Computational Model

ProCAST model for low pressure die casting of wheels (open access)

https://www.mdpi.com/2075-4701/10/11/1418


ProCAST model for counter pressure casting of suspension parts

Modelling of an industrial die casting process for the production of aluminum automotive parts (open access)

https://iopscience.iop.org/article/10.1088/1757-899X/861/1/012030/meta


ABAQUS model for thermal stress analysis of die and casting during permanent die casting processes

Toward the development of a thermal-stress model of an industrial counter pressure casting process (open access)

https://iopscience.iop.org/article/10.1088/1757-899X/861/1/012062


Ansys CFD model & analytical model for titanium melt processing

https://www.sciencedirect.com/science/article/pii/S0017931015002173


Ansys CFD model for fundamental research of melting of a solid in a liquid

https://www.sciencedirect.com/science/article/pii/S001793101400814X


Ansys CFD model for the study of the Thermally Related Factors Influencing the Melting/Dissolution of Solids in Liquid Titanium

https://link.springer.com/chapter/10.1007/978-3-319-48237-8_16


Ansys CFD model for dissolution of alloying element

https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118356074.ch109


Ansys Coupled Thermal-Fluid Flow-Multicomponent Model to Simulate the Melting/Dissolution of Solid Ti-Al in Liquid Titanium during Electron Beam Melting:

The 53rd annual Conference of Metallurgists (COM 2014), Conference Proceedings, 2014.