Buchumschlag

Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction

This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift c...

Ausführliche Beschreibung

Gespeichert in:
1. Verfasser: Lingelbach, Yannick
Format: Online
Sprache:Englisch
Veröffentlicht: KIT Scientific Publishing 2024
Schlagworte:
Data Mining; Case Hardening; Bainitizing; Industrial Heattreatment; Machine Learning; Datenanalyse; Einsatzhärten; Bainitisieren; Industrielle Wärmebehandlung; Maschinelles Lernen
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials
Online-Zugang:https://library.oapen.org/handle/20.500.12657/92444
Tags: Tag hinzufügen
Keine Tags, Fügen Sie das erste Tag hinzu!
Zusammenfassung:This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework.

Ähnliche Einträge