Master’s Student In Assembly (F/M/X)

Key Skills

Algorithms, Amazon Athena, Amazon Simple Storage Service (S3), AWS, AWS Glue, Data Analysis, IT, Machine learning techniques, PowerBI, Python Programming

Job Description

Only highly professional processes in dynamic teams produce innovative cutting-edge technology. But driving pleasure is realized with us from development to production, above all, with fun at work and enthusiasm for the joint project. That's why we not only give students the opportunity to listen, but also to have a say and think ahead.

We, the BMW Group, offer you an exciting and varied master's thesis in the field of high-voltage battery production in Dingolfing.

In this area we are responsible for the production of innovative high-voltage storage systems. Your task as a master's student in the field of high-voltage battery production is the development and introduction of a concept for preventive maintenance using an existing key figure system Smart Maintenance during ramp-up and in series operation of high-voltage battery production. The objective here is an analysis and visualization of the existing fault documentation from the existing key figure system Smart Maintenance in order to derive preventive maintenance/improvement measures and in this sense to avoid or reduce future faults in the high-voltage storage production.

What awaits you?

• Your task is to carry out internal and external research with regard to existing analysis and visualization options as well as existing systems in relation to the objective
• As part of your master's thesis, you will identify relevant target values ​​and their correlation depending on the production facilities and the associated savings potential for the existing reference system and emerging production systems
• An important aspect is the complementation of missing data/flows, which are required for an in-depth analysis and the preventive derivation of maintenance/improvement measures
• At the same time, you transfer your concept into a system that automates the previous analyzes and visualizes the results for the stakeholders. You do this taking into account the stakeholder requirements, the boundary conditions of the production system and considering the identified production facilities.
• Furthermore, you develop or derive a process based on the developed system for the inclusion of stakeholders for the productive and maintenance operation of the system
• The completion of the development and validation of the system is the implementation of a pilot project in a selected production line of the high-voltage battery production
• At the end of your master's thesis, you will lay the foundation for further scientific work by identifying and developing further development options for the system under the term predictive maintenance (deriving recommendations for action through predictive data analysis)

Please note that you must ensure that your final thesis is supervised by a college/university.

what do you bring

• Studies in a technical environment (industrial engineering, mechanical engineering, electrical engineering and information technology, or similar).
• First experiences in the production environment and the use of AWS (Athena, Glue, S3) and PowerBI.
• Extensive experience in data analysis with Python or similar programming languages ​​and the implementation of machine learning algorithms.
• Ability to work in a team, motivation and creative drive.
• assertiveness and initiative.
• Fast, analytical perception and a high affinity for new IT systems.

What do we offer you?

• Comprehensive mentoring & onboarding.
• Personal & professional development.
• Work-life balance & flexible working hours.
• Attractive remuneration.
• Apartments (at the Munich location).
• And much more see jobs/waswirbieten .

Do you enjoy learning new things and actively supporting our department? Apply now!

At the BMW Group, we see diversity and inclusion in all its dimensions as a strength for our teams. Equal opportunities are of particular concern to us, and the equal treatment of applicants and employees is a fundamental principle of our corporate policy. Therefore, our recruiting decisions are also based on their personality, experience and skills.

More about diversity at the BMW Group at bmwgroup.jobs/variety .