Master Thesis : Data-driven Optimal Control of an Additive Manufacturing Process

Siemens AG; München; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

Join a leading company for your Master's thesis and work on cutting-edge projects in electrification and automation. Collaborate with experts while gaining insights into various departments. This opportunity allows you to contribute to innovative solutions in additive manufacturing and control systems.

Qualifikationen

• Currently enrolled in a master's degree program.
• Experience in designing control systems.
• Good knowledge of additive manufacturing.

Aufgaben

• Conduct literature review on WAAM processes.
• Develop an MPC strategy for WAAM using LSTM.
• Gather data on process parameters from experiments.

Kenntnisse

MATLAB

Python

AI Models

Analytical Thinking

Teamwork

Ausbildung

Master's Degree in Automation Engineering

Master's Degree in Electronic Engineering

Master's Degree in Mechanical Engineering

Master's Degree in Robotics

Master's Degree in Physics

Tools

Git

Jobbeschreibung

Do you like the sound of finding the smartest solution side by side with professionals and experts? If so, complete your bachelor’s or master’s thesis with us. We can help you to combine knowledge, discover connections, and formulate ideas. When you join our team, you will gain an insight into a range of departments and processes. It is a chance like no other to break new ground as we head into the future of electrification, automation, and digitalization. Seize this opportunity today!

Change the future with us.

1. Conduct a literature review on data-driven control and optimization methods in additive manufacturing, specifically focusing on Wire Arc Additive Manufacturing (WAAM) processes.
2. Define the specific gaps in current WAAM process control research, particularly in data-driven control approaches (e.g., the lack of robust models, challenges in control of melt pool heat, layer height consistency).
3. Gather data on process parameters and outputs from experiments.
4. Use the collected data to train an LSTM model that accurately represents the WAAM process dynamics for use in a Model Predictive Control (MPC) framework.
5. Develop an MPC strategy for the WAAM process, using the LSTM plant model as the basis for predictive control.
6. You will work within a team which includes engineers, students, developers as well as experts for the manufacturing processes.
7. The duration of the Master’s Thesis is based on university regulations (usually a contract with duration of 6 months is issued).

What you need to make real what matters.

1. You are currently enrolled in a master’s degree program in automation engineering, electronic engineering, mechanical engineering, robotics, physics or a related subject.
2. You have experience in designing control systems in MATLAB / Simulink.
3. You have experience in a programming language like Python.
4. You have some understanding of AI models.
5. Good knowledge of additive manufacturing and git is an advantage.
6. Personally, you impress us with a high level of initiative, analytical thinking as well as a structured way of working in a team environment.
7. You have good English skills.

Make your mark in our exciting world at Siemens.

If you wish to find out more about Siemens before applying, please visit our website.

As an equal-opportunity employer, we are happy to consider applicants from all backgrounds.