Pubblicato su stage4eu il: 20/05/2025 Siemens, Master Thesis: Data-driven Optimal Control of an Additive Manufacturing Process
Siemens
Werner-von-Siemens-Straße 1, Munich, Germania
Engineering
Attività:
- Conduct a literature review on data-driven control and optimization methods in additive manufacturing, specifically focusing on Wire Arc Additive Manufacturing (WAAM) processes
- 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)
- Gather data on process parameters and outputs from experiments
- 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
- Develop an MPC strategy for the WAAM process, using the LSTM plant model as the basis for predictive control
- Assess model performance
- You will work within a team which includes engineers, students, developers as well as experts for the manufacturing processes
- The duration of the Master’s Thesis is based on university regulations (usually a contract with duration of 6 months is issued)
Requisiti principali:
- - You are currently enrolled in a master’s degree program in automation engineering, electronic engineering, mechanical engineering, robotics, physics or a related subject
- You have experience in designing control systems in MATLAB/Simulink
- You have experience in a programming language like Python
- You have some understanding of AI models
- Good knowledge of additive manufacturing and git is an advantage
- Personally, you impress us with a high level of initiative, analytical thinking as well as a structured way of working in a team environment
- You have good English skills
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