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

TN Germany; München; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading company offers a master thesis opportunity in Munich focused on data-driven control in additive manufacturing. This position involves working on literature reviews, experimental data collection, and developing control strategies, providing valuable experience alongside industry professionals.

Qualifikationen

• Enrolled in a relevant master's program.
• Experience with MATLAB/Simulink and Python.
• Understanding of AI models and additive manufacturing is advantageous.

Aufgaben

• Review literature on data-driven control and optimization in WAAM.
• Collect data from experiments and train an LSTM model.
• Develop an MPC strategy using the LSTM model.

Kenntnisse

Control system design

Python programming

AI models

Additive manufacturing

Analytical thinking

Teamwork skills

Good English skills

Ausbildung

Master's program in automation engineering, electronic engineering, mechanical engineering, robotics, or related field

Tools

MATLAB/Simulink

git

Jobbeschreibung

Job Title: Master Thesis: Data-driven Optimal Control of an Additive Manufacturing Process, Munich

This is a master thesis opportunity in Munich focusing on data-driven control in additive manufacturing, specifically Wire Arc Additive Manufacturing (WAAM). The position requires EU work permit and offers a limited employment mode.

Job Details

• Client: Siemens
• Location: Munich, Germany
• Job Category: Other
• Job Reference: 90e96d25f84d
• Job Views: 2
• Posted: 26.05.2025
• Expiry Date: 10.07.2025

Job Description

This master thesis offers an opportunity to work alongside professionals and experts in the field of electrification, automation, and digitalization. The project involves conducting a literature review on data-driven control methods in additive manufacturing, identifying gaps in current research, gathering experimental data, training an LSTM model for process dynamics, and developing an MPC strategy based on this model.

Responsibilities

• Review literature on data-driven control and optimization in WAAM
• Identify research gaps in WAAM process control
• Collect data from experiments
• Train an LSTM model for WAAM process dynamics
• Develop an MPC strategy using the LSTM model
• Collaborate within a multidisciplinary team

Qualifications

• Enrolled in a master's program in automation engineering, electronic engineering, mechanical engineering, robotics, physics, or related field
• Experience with control system design in MATLAB/Simulink
• Proficiency in Python programming
• Understanding of AI models
• Knowledge of additive manufacturing and git is advantageous
• Initiative, analytical thinking, and teamwork skills
• Good English skills

Additional Information

Duration typically 6 months, aligned with university regulations. For more information about Siemens, visit our website. We are an equal-opportunity employer.