Background:
The expanding demand for batteries, driven by the surge in electric vehicles and renewable energy solutions, necessitates a thorough examination of maintenance practices within battery factories. Scania, an industrial leader automotive industry, has recently built their own battery factory. This master's thesis proposal aims to conduct a state-of-the-art literature study, with a particular focus on data-driven decision-making, the relationship between maintenance and quality, and the integral role of humans in the loop. The primary goal is to identify potential use cases for in-depth investigation, offering insights into the optimization of maintenance processes and the symbiotic connection between data, product quality, and human expertise within Scania.

Assignment:
The objective of this master thesis is to conduct an in-depth literature review and case study at Scania's battery factory, to understand the current state-of-the-art in maintenance, particularly in relation to data-driven decision-making. The student(s) also explore the interaction between maintenance processes and product quality, uncovering synergies and challenges, and the critical role of human expertise in maintenance decisions. Expected outcomes include:

-    A comprehensive understanding of the state-of-the-art in maintenance practices within battery manufacturing, focusing on data-driven decision-making, quality relations, and human involvement
-    Identification of key factors influencing the relationship between maintenance and product quality
-    Selection of specific use cases for in-depth study, providing a foundation for further research and practical implementation

What We Offer:
-    Direct collaboration with a leading company in the automotive sector.
-    Access to real production environments.
-    Mentorship from experienced professionals.
-    Opportunity to contribute to cutting-edge research with real-world industrial applications.

Education and time plan:
Education: Master’s program in production engineering, Industrial or Automation Engineering, Data Science.

Qualifications: Understanding of maintenance practices and  data-analysis

Number of students: 1
Start date: January 2025
Estimated time needed: 20 weeks

Contact persons and supervisors:

Mariano Coll, mariano.Coll@scania.com

Maheswaran Gopalakrishnan, maheshwaran.gopalakrishnan@scania.com

Application:

Your application must include a CV, personal letter and transcript of grades.

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.

Thesis Worker