Microstructure-Based Finite-Element Prediction of Surface Integrity with Bayesian-Informed Wear States

Application to Longitudinal Turning of AISI 4140

von Germán González Fernández

155 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

Surface integrity plays a decisive role in the functional performance, fatigue life, and reliability of machined components. This dissertation presents a physics-informed and uncertainty-aware framework for predicting wear-dependent surface integrity during longitudinal turning of AISI 4140 steel. The approach combines tool-integrated thin-film sensors, experimentally validated two- and three-dimensional finite-element simulations, microstructure-based modelling of dynamic recrystallisation, and Bayesian inference for tool-wear estimation. By integrating sensing, physics-based simulation, surrogate modelling, and probabilistic inference, the proposed framework enables uncertainty-aware prediction of thermomechanical loads, microstructural evolution, and ultrafine-grained surface-layer formation. The resulting hybrid soft-sensor architecture establishes a foundation for future process-accompanying monitoring, digital twins, and closed-loop machining applications. The dissertation is intended for researchers and engineers working in manufacturing science, machining, finite-element modelling, surface integrity, and intelligent production systems.

• Reihe: Forschungsberichte aus dem wbk, Institut für Produktionstechnik Universität Karlsruhe
• Themen: Technologie, Ingenieurswissenschaft, Landwirtschaft, Industrieprozesse Maschinenbau und Werkstoffe Fertigungstechnik und Ingenieurwesen
• ISBN: 9783819109096
• Sprache: Englisch
• Erscheinungsdatum: 19.10.2026
• Größe: 21 x 14.8 cm
• Verlag: Shaker