Abstract
In metastable austenitic steels like AISI 304, martensitic surface layers can be created by cryogenic external longitudinal turning which results in a hardening of the surface. It is possible to identify the correlation between process parameters and the formation of deformation-induced martensite with machine learning methods. Based on this, evolutionary algorithms are used to determine the appropriate process parameters in order to achieve different defined martensite contents. In order to be able to even control the martensite content within the turning process, an eddy current sensor is integrated into the machine tool. In-situ measurements can be conducted and are presented here.
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