Master's Thesis: Adapting MLOps for Integrating AI/ML in Maintenance - Remote

Overview

The goal of this master's thesis is to adapt MLOps approaches specifically for the application case of maintenance, enabling effective use of AI/ML in maintenance processes supported by MLOps.

In Short

• Literature and market research on current trends and technologies in MLOps and their application in maintenance.
• Analysis of specific requirements for AI/ML models in maintenance operations.
• Development of a tailored MLOps approach to facilitate the integration of AI/ML in maintenance.
• Derivation of recommendations for action and creation of practical documentation.

Requirements

• Studying Industrial Engineering, Mechanical Engineering, Computer Science, or similar.
• Very good German and English language skills, both written and spoken.
• Independent, committed, careful, and goal-oriented working style.
• Proficient in common MS Office programs.

Benefits

• Interesting and challenging tasks.
• Engagement with practical and highly relevant research topics.
• Structured support with regular exchanges, either digitally or on-site, and constructive feedback loops.
• Promotion of independent working style and flexible scheduling.
• A motivated team and a modern workplace at the Smart Logistics Cluster.