A process-reliable tailoring of subsurface properties during cryogenic turning using dynamic process control

authored by: Berend Denkena, Bernd Breidenstein, Hans Jürgen Maier, Vannila Prasanthan, Lara Vivian Fricke, Felix Zender, Hai Nam Nguyen, Stefan Zwoch, Marcel Wichmann, Sebastian Barton
Abstract: Considering the current demands for resource conservation and energy efficiency, innovative machining concepts and increased process reliability have a significant role to play. A combination of martensitic hardening of the subsurface and near-net-shape manufacturing represent a great potential to produce components with wear-resistant subsurfaces in an energy- and time-saving way. Within the scope of the present study, the influence of cryogenic machining of metastable austenitic steel on the martensitic transformation and surface quality was investigated. Different cooling strategies were used. A soft sensor based on eddy current in-process measurements was used to determine and subsequently affect the martensitic transformation of the subsurface. The feed rate and component temperature were identified as significant factors influencing the martensitic transformation. However, a high feed rate leads to an increase in surface roughness, and thus to a reduction in component quality. For this reason, a roughing process for achieving maximum martensitic transformation was carried out first in the present study and then a reduction in the surface roughness by maintaining the martensitic subsurface content was aimed for by a subsequent finishing process. With the knowledge generated, a dynamic process control was finally set up for designing the turning process of a required subsurface condition and surface quality.
Organisation(s): Institute of Production Engineering and Machine Tools
Institute of Materials Science
Type: Article
Journal: Production Engineering
Volume: 18
Pages: 233–251
No. of pages: 19
ISSN: 0944-6524
Publication date: 04.2024
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Mechanical Engineering, Industrial and Manufacturing Engineering
Sustainable Development Goals: SDG 7 - Affordable and Clean Energy
Electronic version(s): https://doi.org/10.1007/s11740-023-01244-0 (Access: Open)

BibTeX

@article{1934f41db9374ebba57f33998da7437c,
title = "A process-reliable tailoring of subsurface properties during cryogenic turning using dynamic process control",
abstract = "Considering the current demands for resource conservation and energy efficiency, innovative machining concepts and increased process reliability have a significant role to play. A combination of martensitic hardening of the subsurface and near-net-shape manufacturing represent a great potential to produce components with wear-resistant subsurfaces in an energy- and time-saving way. Within the scope of the present study, the influence of cryogenic machining of metastable austenitic steel on the martensitic transformation and surface quality was investigated. Different cooling strategies were used. A soft sensor based on eddy current in-process measurements was used to determine and subsequently affect the martensitic transformation of the subsurface. The feed rate and component temperature were identified as significant factors influencing the martensitic transformation. However, a high feed rate leads to an increase in surface roughness, and thus to a reduction in component quality. For this reason, a roughing process for achieving maximum martensitic transformation was carried out first in the present study and then a reduction in the surface roughness by maintaining the martensitic subsurface content was aimed for by a subsequent finishing process. With the knowledge generated, a dynamic process control was finally set up for designing the turning process of a required subsurface condition and surface quality.",
keywords = "Cryogenic turning, Deformation-induced martensitic transformation, Dynamic process control, Eddy-current sensor, Subsurface properties",
author = "Berend Denkena and Bernd Breidenstein and Maier, {Hans J{\"u}rgen} and Vannila Prasanthan and Fricke, {Lara Vivian} and Felix Zender and Nguyen, {Hai Nam} and Stefan Zwoch and Marcel Wichmann and Sebastian Barton",
note = "Funding information: Open Access funding enabled and organized by Projekt DEAL. The scientific work has been supported by the Deutsche Forschungsgemeinschaft (DFG) within the research priority program SPP 2086 (grant project number 401800578). The authors thank DFG for funding.",
year = "2024",
month = apr,
doi = "10.1007/s11740-023-01244-0",
language = "English",
volume = "18",
pages = "233–251",
journal = "Production Engineering",
issn = "0944-6524",
publisher = "Springer Verlag",
number = "2",
}