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analysing the influence of the main machining parameters on the dynamic behaviour of cutting, with the objective of identifying instability conditions and supporting process optimization. This work plan is
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within the framework of project PROMisH - Potential of Rheologically-Optimized Magnetic Emulsions in Hemotherapy, with nº 16207, and the operation code at the Funds Platform COMPETE2030-FEDER-00736400 and
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samples. The candidate will be involved in developing, optimizing, and validating advanced analytical methodologies, applying them to analyze environmental samples, processing and interpreting data using
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than 14/20 (1 point); B. Knowledge of Interactive Systems Design, Cyber-Physical Systems, Predictive Maintenance Systems, Automation, Machine Learning and Artificial Intelligence, Sensor Networks
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-vision algorithms with edge-computing processing for the automatic detection of non-conformities. Machine-learning techniques will be applied to optimize cutting parameters, and the module will be