Details
| Original language | English |
|---|---|
| Pages (from-to) | 170-175 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 108 |
| Issue number | C |
| Early online date | 1 Jun 2022 |
| Publication status | Published - 2022 |
| Event | 6th CIRP Conference on Surface Integrity, CSI 2022 - Lyon, France Duration: 8 Jun 2022 → 10 Jun 2022 |
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.
Keywords
- cryogenic machining, eddy current testing, metastable austenitic steel, modelling, surface integrity
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 108, No. C, 2022, p. 170-175.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Setting of deformation-induced martensite content in cryogenic external longitudinal turning
AU - Denkena, Berend
AU - Breidenstein, Bernd
AU - Dittrich, Marc André
AU - Wichmann, Marcel
AU - Nguyen, Hai Nam
AU - Fricke, Lara Vivian
AU - Zaremba, David
AU - Barton, Sebastian
N1 - Funding Information: The scientific work has been supported by the DFG within the research priority program SPP 2086 (grant project number 401800578). The authors thank the DFG for this funding and intensive technical support.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - cryogenic machining
KW - eddy current testing
KW - metastable austenitic steel
KW - modelling
KW - surface integrity
UR - http://www.scopus.com/inward/record.url?scp=85134620217&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2022.03.030
DO - 10.1016/j.procir.2022.03.030
M3 - Conference article
AN - SCOPUS:85134620217
VL - 108
SP - 170
EP - 175
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
IS - C
T2 - 6th CIRP Conference on Surface Integrity, CSI 2022
Y2 - 8 June 2022 through 10 June 2022
ER -