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Conduct a literature review on computer vision models used in real-time process control in additive manufacturing, specifically focusing on Wire Arc Additive Manufacturing (WAAM) processes Define the specific gaps in current WAAM process monitoring research, particularly in computer vision models (e.g., the lack of robust models, challenges in monitoring of melt pool heat, layer height consistency) Gather data on process parameters and outputs from experiments Use the collected data to train an AI model that accurately represents the WAAM process dynamics Develop a Deep Learning model for monitoring the selected process parameters You will work within a team which includes engineers, students, developers as well as experts for the manufacturing processesWhat you need to make real what matters.
Currently you are enrolled in a master’s degree program in automation engineering, electronic engineering, mechanical engineering, robotics, physics or a related subject You have good experience in Computer Vision and AI You have experience in a programming language like Python Good knowledge of additive manufacturing and git is an advantage Experience in C/C++ deployment of real-time AI models is a big plus. 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 skillsMake your mark in our exciting world at Siemens.
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