An explainable artificial intelligence model for predictive maintenance and spare parts optimization
Maintenance strategies are vital for industrial and manufacturing systems. This study considers a proactive maintenance strategy and emphasizes using analytics and data science. We propose an Explainable Artificial Intelligence (XAI) methodology for predictive maintenance. The proposed method utiliz...
Saved in:
Main Authors: | Ufuk Dereci, Gülfem Tuzkaya |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2024-12-01
|
Series: | Supply Chain Analytics |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2949863524000219 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
OPTIMIZATION OF THE PROCESSES OF PRODUCTION OF SPARE PARTS FOR MOTOR VEHICLES
by: Tatiana V. Avetisyan, et al.
Published: (2024-06-01) -
Predictive and Explainable Artificial Intelligence for Neuroimaging Applications
by: Sekwang Lee, et al.
Published: (2024-10-01) -
Detecting Adversarial Attacks in IoT-Enabled Predictive Maintenance with Time-Series Data Augmentation
by: Flora Amato, et al.
Published: (2024-11-01) -
Intelligent Health Management System for Rail Transit Signaling System Power Supply
by: GU Zhenhao
Published: (2024-11-01) -
A task‐centric knowledge graph construction method based on multi‐modal representation learning for industrial maintenance automation
by: Zengkun Liu, et al.
Published: (2024-12-01)