Digital Twin and virtual sensing strategies for metal casting processes and products

Katholieke Universiteit Leuven
December 02, 2022
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Digital Twin and virtual sensing strategies for metal casting processes and

products

(ref. BAP-2022-744)

Last modification : Tuesday, October 18, 2022

The research is hosted by the KU Leuven Mecha(tro)nic System Dynamics division (LMSD), which currently counts >100 researchers. This research track is supervised by prof. Frank Naets (https: // www. kuleuven.be/wieiswie/en/person/00055809 ). The research group has a long track record of combining excellent fundamental academic research with industrially relevant applications, leading to dissemination in both highly ranked academic journals as well as on industrial fora. More information on the research group can be found on the website: https: // www. mech.kuleuven.be/en/research/mod/about and our linkedIn page: https: // www. linkedin.com/showcase/noise-&-vibration-research-group. This research track is embedded in a European collaborative research project with industry, and where the LMSD division is leading the project.

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Project

This PhD is part of a project aiming to develop a novel approach for developing digital twins and virtual sensing of metal casting processes and how they influence the performance of the resulting parts. These production methods are common in many high-end mechanical applications (e.g. automotive), but a shift towards lower defect products and the use of recycled materials puts a large strain on the existing approaches. This project aims to achieve Digital Twin where a simulation model for a product can be exploited and updated for both the production process monitoring (through available sensors on the machine), and for the assessment of final part performance (strength, residual stress, etc.).

As a researcher you will investigate novel methods to combine thermo- mechanical models (and their reduced-order versions) of various structures on the one hand with the available casting process information and measurements, and on the other hand with the end-of-line testing data. You will develop the parameterized numerical models to describe the process and part performance. Through model order reduction methods you will aim to bring down the computational cost sufficiently such that these model can be deployed online during the production process of a particular part. You will exploit the parameterization of the model both for updating it with respect to in- process deviations, as well as to characterize variations in the material properties. During this research you will be in continuous interaction with industry to assess how the developments can fit in and aid existing workflows.

Profile

If you recognize yourself in the story below, then you have the profile that fits the project and the research group:

  • I have a master degree in engineering, physics or mathematics and performed above average in comparison to my peers.
  • I am proficient in written and spoken English.
  • During my courses or prior professional activities, I have gathered some basic experience with numerical modelling methods and optimization methods.
  • I have a good background in finite-element methods (both theory and application) for mechanical problems (thermal and structural).
  • I have notions of control theory and estimation.
  • I have experience end/or am interested in combining numerical and experimental work.
  • I am proficient in programming basic methods in Matlab.
  • As a PhD researcher of the KU Leuven Noise and Vibration Research Group I perform research in a structured and scientifically sound manner. I read technical papers, understand the nuances between different theories and implement and improve methodologies myself.
  • Based on interactions and discussions with my supervisors and the colleagues in my team, I set up and update a plan of approach for the upcoming 1 to 3 months to work towards my research goals. I work with a sufficient degree of independence to follow my plan and achieve the goals. I indicate timely when deviations of the plan are required, if goals cannot be met or if I want to discuss intermediate results or issues.
  • In frequent reporting, varying between weekly to monthly, I show the results that I have obtained and I give a well-founded interpretation of those results. I iterate on my work and my approach based on the feedback of my supervisors which steer the direction of my research.
  • I feel comfortable to work as a team member and I am eager to share my results to inspire and being inspired by my colleagues.
  • I value being part of a large research group which is well connected to the machine and transportation industry and I am eager to learn how academic research can be linked to industrial innovation roadmaps.
  • During my PhD I want to grow towards following up the project that I am involved in and representing the research group on project meetings or conferences. I see these events as an occasion to disseminate my work to an audience of international experts and research colleagues, and to learn about the larger context of my research and the research project.
  • Offer
  • A remuneration package competitive with industry standards in Belgium, a country with a high quality of life and excellent health care system.
  • An opportunity to pursue a PhD in Mechanical Engineering, typically a 4 year trajectory, in a stimulating and ambitious research environment.
  • Ample occasions to develop yourself in a scientific and/or an industrial direction. Besides opportunities offered by the research group, further doctoral training for PhD candidates is provided in the framework of the KU Leuven Arenberg Doctoral School (https: // set.kuleuven.be/phd), known for its strong focus on both future scientists and scientifically trained professionals who will valorise their doctoral expertise and competences in a non-academic context. More information on the training opportunities can be found on the following link: https: // set.kuleuven.be/phd/dopl/whytraining.
  • A stay in a vibrant environment in the hearth of Europe. The university is located in Leuven, a town of approximately 100000 inhabitants, located close to Brussels (25km), and 20 minutes by train from Brussels International Airport. This strategic positioning and the strong presence of the university, international research centers, and industry, lead to a safe town with high quality of life, welcome to non-Dutch speaking people and with ample opportunities for social and sport activities. The mixture of cultures and research fields are some of the ingredients making the university of Leuven the most innovative university in Europe (https: // nieuws.kuleuven.be/en/content/2018/ku-leuven-once-again-tops- reuters-ranking-of-europes-most-innovative-universities). Further information can be found on the website of the university: https: // www. kuleuven.be/english/living
  • Interested?

    For more information please contact Prof. dr. Frank Naets, tel.: +32 16 37 26 93, mail: frank.naets@kuleuven.be with in the topic MetaFacturingvacancy.

    KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

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