Master's thesis; Data-Driven Digital Models for Enhancing efficiency and forecasting in Battery Cell Manufacturing

We are looking for a Master of Science student for a thesis project at the System Integration unit at RISE. The unit is part of the division Digital Systems.

Background
The energy landscape is transforming towards sustainability, with a pivotal role played by advancements in battery digital technology. In this context, we offer an exciting opportunity for a Master's thesis focused on the digitalization of battery cell manufacturing processes.

Thesis Description
This thesis focuses on developing a data-driven digital model for the battery cell manufacturing process, integrating AI and traceability methods. The model will be based on data from industry or literature, aiming to capture and forecast essential aspects of battery cell manufacturing through comprehensive data integration and modeling.

The main objective is to establish a proof of concept (PoC) that demonstrates the viability and effectiveness of using a data-driven digital model and AI to transform battery cell production. This includes creating a detailed digital model that maps interactions between various systems within the manufacturing process. By identifying and modeling specific subsystems, the model provides in-depth insights into critical manufacturing areas. Additionally, AI-driven models will predict potential bottlenecks, facilitating proactive decision-making and reducing manufacturing downtime.

Terms
Expected start: January 2025 (flexible).
Duration: 20 weeks.
Location: Your university place and/or RISE ( Luleå, Kista, Mölndal).
Credits: 30 ECTS (academic credits) in agreement with your university's thesis advisor.
Benifits: Compensation upon approved thesis completion.

Who You Are
We expect you to have a solid knowledge of machine learning theory and good programming skills (especially Python). Keen interest in sustainable energy technologies and data-driven modeling and solving complex problems.

Welcome with your application!
If you need more information, please contact Dr. Madhav Mishra (madhav.mishra@ri.se). Applications should include (1) a brief personal letter, (2) a CV, and (3) a recent grade transcript. Candidates are encouraged to send their application as soon as possible but at the latest by 2024-12-05. Please apply directly through this portal (We do not accept applications via email).