Master-thesis model-based Process Monitoring and Optimisation of Quality Features in High-pressure Die-casting

vor 2 Wochen


Wien, Österreich Austrian Institute of Technology Vollzeit

As **Austria's largest research and technology organisation** for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria's leading research institution at the highest international level and to make a positive contribution to the economy and society. The Master Thesis is part of the lighthouse project** AI Enabled Sustainable Automation**, where new methods and technologies are developed to enable zero-defect manufacturing in high-pressure die-casting. In die casting, molten metal is transported by a piston into the mould, while a temperature control unit continuously controls its temperature. In the tempered mould, the solidification of the metal occurs. All these processes have an impact on the quality of the die-cast part and the efficiency of the die-casting process. In this Master Thesis, we are conducting research on modelling, monitoring and optimising the quality of die-cast parts with the aim of reducing scrap and increasing resource efficiency. MASTER-THESIS "MODEL-BASED PROCESS MONITORING AND OPTIMISATION OF QUALITY FEATURES IN HIGH-PRESSURE DIE-CASTING" CENTER FOR VISION, AUTOMATION & CONTROL - The main goal of this master’s thesis is to develop a strategy for process monitoring and optimisation (optional). - Under the guidance of your interdisciplinary team, you will carry out a literature search, develop data-driven models for quality features depending on machine settings and variables and a model-based strategy for process monitoring and optimisation. - You will gain knowledge in quality control and analyse multimodal data (e.g. rational data, timeseries data, images). - You will implement the mathematical models and the monitoring and optimisation algorithms in Python / MATLAB. - You will accumulate experience in a research field, that deals with the triple transition. - You will gain experience working alongside an international team of engineers and scientists while expanding your professional network. **Your qualifications as an Ingenious Partner**: - Ongoing master's studies in the field of Automation & Control, Data Science, Electrical Engineering, Mechanical Engineering, Mechatronics, Physics or Mathematics - Excellent programming skills in Python, knowledge in MATLAB is a plus - First experience in PyTorch or Tensorflow are beneficial - Excellent technical understanding & analytical capabilities - High level of commitment and team spirit - Good knowledge of German and/or English in word and writing **What to expect**: - **Duration of the master’s thesis project**: 6 months - **Start date**: as soon as possible - EUR 603,04 gross per month for 12 hours/week based on the collective agreement. As a research institution, we are familiar with the supervision and execution of master theses, and we are looking forward to supporting you accordingly



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