Development of a methodical approach for uncertainty quantification and meta-modeling of surface hardness in white layers of longitudinal turned AISI4140 surfaces
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Daniel Gauder
Daniel Gauder is currently a Research Associate at the Institute of Production Sciences (wbk) at the Karlsruhe Institute of Technology (KIT) and holds a B. Sc. in Business Administration and Engineering and an MBA in Production Management. His research interests lie in the field of process optimization through the implementation of in process measurement technology in machine tools.
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Michael Biehler
Michael Biehler is a research assistant at the wbk Institute for Production Engineering at the Karlsruhe Institute of Technology (KIT).
Johannes Gölz is a research assistant at the wbk Institute for Production Engineering at the Karlsruhe Institute of Technology (KIT).
Benedict Stampfer has been a research associate of the research group ‘manufacturing and materials technology’ at wbk Institute of Production Science since 2017. His research areas include cooling strategies and control concepts of machining processes as well as surface engineering.
David Böttger has studied mechatronics with specialization in the field of sensor technology at University of Applied Sciences in Saarbruecken. During his bachelor and master studies he was working as a research assistant in the field of laser welding processes, air- and structure-borne ultrasound emissions. Since 2017 he is working as a scientific associate in the department “Production integrated NDT” with focus in multidimensional sensor technologies for process monitoring applications such as high frequency acoustic and micromagnetic NDT-techniques.
Benjamin Häfner is team leader at the Institute for Production Science (wbk) at Karlsruhe Institute of Technology (KIT) for the areas of global production strategies and quality assurance.
Bernd Wolter studied Material Science at University of Saarland. He made his PhD in Applications of One-Sided Nuclear Magnetic Resonance for Material Characterization. In 2001 he was awarded with the Berthold Prize of the DGZfP (German Society for Non-Destructive Testing). Since 2002 he is head of department for Production Integrated NDT at the Fraunhofer-Institute for Nondestructive Testing. His research is focussed to sensor-based quality monitoring and control in production.
Volker Schulze has been a full professor for Manufacturing and Materials Technology at the Institute for Production Science at Karlsruhe Institute of Technology (KIT) since April 2010. Parallelly, he is director at the Institute of Applied Materials at KIT. He is member of CIRP International Academy for Production Engineering and Spokesperson of the Research Priority Program 2086 of DFG. Research Interests include machining, additive manufacturing, heat treatment and mechanical surface treatments.
Prof. Dr.-Ing. Gisela Lanza is member of the management board at the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology (KIT). She heads the Production Systems division dealing with the topics of global production strategies, production system planning, and quality assurance in research and industrial practice.
Abstract
The formation of thermally and mechanically induced near-surface microstructures in the form of white layers leads to different hardness properties in these areas. Therefore, this paper conducts systematic surface hardness measurements and uncertainty quantification utilizing the Monte Carlo Method (MCM) in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM). Furthermore, several meta-models describing the hardness course in relationship to the material depth are used to model this nonlinear relationship via machine learning. The evaluation and selection of the optimal model considers the trade-off between measurement uncertainty and prediction quality in terms of mean squared error (MSE). The resulting measurement uncertainty is to be used for the calibration of a non-destructive micromagnetic material sensor. This will then be implemented for in-process monitoring in the outer diameter longitudinal turning process. This should make it possible to detect white layers during machining and to avoid them accordingly by controlling the machine parameters. By means of a soft sensor, the corresponding target value is to be derived from the micromagnetic material sensor measurement.
Zusammenfassung
Die Entstehung thermisch und mechanisch induzierter oberflächennaher Mikrostrukturenin Form von weißen Schichten führt in diesen Bereichen zu unterschiedlichen Härteeigenschaften. In diesem Beitrag werden Ergebnisse von systematischen Oberflächenhärtemessungen sowie eine Unsicherheitsanalyse über die Monte-Carlo-Methode (MCM) gemäß dem Guide to the Expression of Uncertainty in Measurement (GUM) durchgeführt. Mehrere Meta-Modelle, die den Härteverlauf in Abhängigkeit der Tiefe darstellen, werden zur Modellierung des nichtlinearen Verlaufs durch maschinelles Lernen verwendet. Die Bewertung über die Minimierung der Fehlerquadratsumme (MSE) zur Auswahl des optimalen Modells stellt einen Kompromiss zwischen Messunsicherheit und Vorhersagequalität dar. Über die resultierende Messunsicherheit wird die Kalibrierung für einen auf mikromagnetischer Basis arbeitenden Materialsensor realisiert. Dieser wird daraufhin für die Prozessüberwachung im Außendurchmesser-Längsdrehprozess eingesetzt. Die Entstehung weißer Randzonen während der Bearbeitung kann so erkannt und durch entsprechende Parameterwahl vermieden werden. Über einen implementierten Softsensor soll aus der mikromagnetischen Materialcharakterisierung der entsprechende Sollwert abgeleitet werden.
Funding statement: The scientific work has been supported by the DFG within the research priority program SPP 2086 (SCHU 1010/65-1, LA 2351/46-1, WO 903/4-1). The authors thank the DFG for this funding and intensive technical support.
About the authors
Daniel Gauder is currently a Research Associate at the Institute of Production Sciences (wbk) at the Karlsruhe Institute of Technology (KIT) and holds a B. Sc. in Business Administration and Engineering and an MBA in Production Management. His research interests lie in the field of process optimization through the implementation of in process measurement technology in machine tools.
Michael Biehler is a research assistant at the wbk Institute for Production Engineering at the Karlsruhe Institute of Technology (KIT).
Johannes Gölz is a research assistant at the wbk Institute for Production Engineering at the Karlsruhe Institute of Technology (KIT).
Benedict Stampfer has been a research associate of the research group ‘manufacturing and materials technology’ at wbk Institute of Production Science since 2017. His research areas include cooling strategies and control concepts of machining processes as well as surface engineering.
David Böttger has studied mechatronics with specialization in the field of sensor technology at University of Applied Sciences in Saarbruecken. During his bachelor and master studies he was working as a research assistant in the field of laser welding processes, air- and structure-borne ultrasound emissions. Since 2017 he is working as a scientific associate in the department “Production integrated NDT” with focus in multidimensional sensor technologies for process monitoring applications such as high frequency acoustic and micromagnetic NDT-techniques.
Benjamin Häfner is team leader at the Institute for Production Science (wbk) at Karlsruhe Institute of Technology (KIT) for the areas of global production strategies and quality assurance.
Bernd Wolter studied Material Science at University of Saarland. He made his PhD in Applications of One-Sided Nuclear Magnetic Resonance for Material Characterization. In 2001 he was awarded with the Berthold Prize of the DGZfP (German Society for Non-Destructive Testing). Since 2002 he is head of department for Production Integrated NDT at the Fraunhofer-Institute for Nondestructive Testing. His research is focussed to sensor-based quality monitoring and control in production.
Volker Schulze has been a full professor for Manufacturing and Materials Technology at the Institute for Production Science at Karlsruhe Institute of Technology (KIT) since April 2010. Parallelly, he is director at the Institute of Applied Materials at KIT. He is member of CIRP International Academy for Production Engineering and Spokesperson of the Research Priority Program 2086 of DFG. Research Interests include machining, additive manufacturing, heat treatment and mechanical surface treatments.
Prof. Dr.-Ing. Gisela Lanza is member of the management board at the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology (KIT). She heads the Production Systems division dealing with the topics of global production strategies, production system planning, and quality assurance in research and industrial practice.
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Articles in the same Issue
- Frontmatter
- Beiträge
- Development of a methodical approach for uncertainty quantification and meta-modeling of surface hardness in white layers of longitudinal turned AISI4140 surfaces
- Optimierung der Sensorpositionierung bei schwingungsbasierter Wälzlagerzustandsüberwachung unter Einbezug von Systemeigenmoden
- Berührungslose Messung von Pitchwinkelabweichungen an Windenergieanlagen aus 150 m Entfernung
- Kontaktlose Durchhangsdetektion an Freileitungen durch Bildverarbeitung
- Novel methodology for turbine gas meters error curve modelling across a wide range of operating parameters
- A simple closed-form model to accurately calculate the electromechanical coupling coefficient of CMUTs
- Force measurement of electrodes on a human head model
Articles in the same Issue
- Frontmatter
- Beiträge
- Development of a methodical approach for uncertainty quantification and meta-modeling of surface hardness in white layers of longitudinal turned AISI4140 surfaces
- Optimierung der Sensorpositionierung bei schwingungsbasierter Wälzlagerzustandsüberwachung unter Einbezug von Systemeigenmoden
- Berührungslose Messung von Pitchwinkelabweichungen an Windenergieanlagen aus 150 m Entfernung
- Kontaktlose Durchhangsdetektion an Freileitungen durch Bildverarbeitung
- Novel methodology for turbine gas meters error curve modelling across a wide range of operating parameters
- A simple closed-form model to accurately calculate the electromechanical coupling coefficient of CMUTs
- Force measurement of electrodes on a human head model
