Open PhD Position

DIGITAL TWINS IN MACHINING AND HYBRID PROCESSES FOR

AN IMPROVED PART QUALITY

Short description of the research work

The research work to be conducted in this Ph.D. aims to design and build digital twins of machining and hybrid processes with the objective to optimize and control the process’s parameters for an increased productivity and an improved part quality. This research work combines several technologies such as: machining, IIoT, and artificial intelligence. Data collected from sensors (IIoT) placed strategically in the process is combined with data generated by physics-based simulations to construct a data-driven model based on Machine Learning. This data-driven model is used in the process’s optimization, which culminates in corrective actions (process control) to achieve an improved part quality in a short production time.

Keywords

Machining, Part quality, Digital Twins; IoT, Machine Learning; Physic-based modelling.

Candidates’ qualifications

We are looking for a highly motivated candidate with a Master’s degree in mechanical engineering. Knowledge on machining, materials science, and machine learning will be considered a strong merit. Other desirable qualifications include sensors (IIoT), optimization-based algorithms, programming (Python), and the numerical simulation.

Requested information

• A description of the research interests and previous research experience.
• CV with a publication list.
• Names of two references.

Starting date

Spring 2025