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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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engineering challenge. Key to success will be the development of cost competitive and reliable methods to produce hydrogen via electrolysis of water/steam driven by green electricity. Hydrogen can be used as a
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decision support systems will increasingly define the future. While significant strides have been made in the development of autonomous systems, their reliability and safety remain key concerns, particularly
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work tasks The applications and communication scenarios in 6G will be challenging due to stringent requirements in terms of latency, reliability, privacy, and efficiency. Furthermore, 6G networks
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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stability. However, the fine-grained monitoring needed for such coordination risks exposing privacy. Although operators collect this information to ensure reliability, current practices seldom embed strong