Optimising industrial efficiency: integrating K-Means clustering and data Science for sustainable manufacturing and waste Reduction
This study investigates the practical application of K-means clustering analysis within industrial settings to optimise machine performance and operational efficiency. By collecting data every minute from 34 machines within a multinational company, we constructed an extensive time-series database. T...
Saved in:
Main Authors: | Thierry Warin, Pierre-Michel d’Anglade, Nathalie de Marcellis-Warin |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2025-12-01
|
Series: | International Journal of Sustainable Engineering |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/19397038.2025.2527300 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Consistency Evaluation Method for Digital Twins in Manufacturing
by: Li Sun, et al.
Published: (2025-01-01) -
Optimising Manufacturing Efficiency: A Data Analytics Solution for Machine Utilisation and Production Insights
by: Saleh Seyedzadeh, et al.
Published: (2025-06-01) -
Navigating the manufacturing, testing and regulatory complexities of regulatory T cells for adoptive cell therapy
by: Larissa A. Pikor, et al.
Published: (2025-07-01) -
Analysis of Wear in the Contact Between the Wheel Tread and the Rail Head: Influence of the Manufacturing Process of Cast and Forged Railway Wheels
by: V.G. Germinari, et al.
Published: (2025-07-01) -
Reducing Delivery Times by Utilising On-Site Wire Arc Additive Manufacturing with Digital-Twin Methods
by: Stefanie Sell, et al.
Published: (2025-06-01)