比利时KU Leuven大学数字孪生博士生招生 - 中国留学基金委项目

The CSC-KU Leuven scholarship programme

Every year the China Scholarship Council (CSC) opens a call for Chinese candidates to apply for a PhD scholarship. Candidates need a research topic and supervisor in order to apply. Candidates can write their own proposal and find a supervisor; or apply within the CSC-KU Leuven scholarship programme. In the CSC-KU Leuven programme, KU Leuven professors in Science, Engineering & Technology formulate research topics to which candidates can apply. The selected candidates will then apply to CSC in February/March. CSC and KU Leuven have agreed to fund up to 50 PhD scholarship positions in Science and Technology to outstanding Chinese applicants. Read more about this scholarship programme on this CSC website (https://www.csc.edu.cn/). 

Candidates should be citizens of the People’s Republic of China at the time of application. Overseas Chinese students may be eligible for application subject to CSC policy at the time.

[2025-23] 

Digital Twins for Circular Economy: Data-Driven Modeling and Production Control for Smart De- and Re-Manufacturing Systems

Keywords: 

Industrial Engineering, Process Mining, Data Mining, Discrete Event Simulation, Industry 4.0, Smart Manufacturing.

Link to the Programme: 

https://set.kuleuven.be/phd/applicants/csc-kuleuven#23

Supervisor: 

Prof. Giovanni Lugaresi

Summary: 

Recently, the de- and re-manufacturing industry has begun to play a crucial role in sustainable resource management, in the development of circular economy, and for the reduction of the environmental impact of industrial systems. However, optimizing these new production paradigms remains a complex challenge due to their intricate processes and varying demands. Indeed, de- and re-manufacturing systems involve workflows with numerous steps, resources, and dependencies, together with a highly unpredictable product variety in input. Traditional production planning, control, and optimization methods are often inadequate in managing the complexity and dynamism of de- and re-manufacturing systems. One of the main reasons is the rapid obsolescence of digital models, together with their low adaptability. There is a pressing need for more data-driven, adaptive, and automated approaches to model generation and process optimization for achieving smart manufacturing systems in the circular economy framework. This research introduces a novel approach using process mining techniques for automated data-driven model generation in de- and re-manufacturing systems.

Research Activities:

• Automated extraction and analysis of production system data: collecting and pre-processing data from various sources within de- and re-manufacturing systems. If needed, synthetic datasets can be generated exploiting validated simulation models.

• Process discovery and system modeling: applying process mining techniques to automatically discover, and model the material flows and main behavior of the systems.

• Performance analysis: evaluating the efficiency and productivity levels of current processes through data-driven analysis.

• Simulation and optimization: developing models for simulation and optimization of de- and re-manufacturing processes. Prediction of future scenario-based system performance exploiting simulation experiments.

• Multi-disciplinary aspects: applying techniques from other fields (e.g., artificial intelligence, machine learning, natural language processing) to enrich model generation techniques.

This research will have a concrete impact on the industry's sustainability goals, economic viability, and competitiveness in the global market.

报名截止期限: 

31 December 2024

报名链接: 

https://set.kuleuven.be/phd/applicants/application

Make sure to fill in the application form before the deadline. Take into account that you can only pre-apply to ONE topic (or to several topics with the same supervisor).

联系方式：

TEL. + 32 16326822; 

MOBILE: + 393479604232

Email: giovanni.lugaresi@kuleuven.be  https://www.kuleuven.be/wieiswie/en/person/00163811

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