Explaining the Anomaly Detection in Additive Manufacturing via Boosting Models and Frequency Analysis

Explaining the Anomaly Detection in Additive Manufacturing via Boosting Models and Frequency Analysis

Anomaly detection is an important feature in modern additive manufacturing (AM) systems to ensure quality of the produced components. Although this topic is well discussed in the literature, current methods rely on black-box approaches, limiting our understanding of why anomalies occur, making compl...

Full description

Saved in:
Bibliographic Details
Main Authors: Mario Vozza, Joseph Polden, Giulio Mattera, Gianfranco Piscopo, Silvestro Vespoli, Luigi Nele
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Mathematics
Subjects:
machine learning
explainable AI
anomaly detection
additive manufacturing
Online Access:https://www.mdpi.com/2227-7390/12/21/3414
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items