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Annop Monsakul. Comparative study of ensemble learning for predictive maintenance in hdd manufacturing. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2025.
Comparative study of ensemble learning for predictive maintenance in hdd manufacturing
Name: Saisuda Nantalek
Organization :
Thai-Nichi Institute of Technology. Faculty of Information Technology
Email :
2463110300@tni.ac.th
Name: Sarayut Nonsiri
Organization :
Thai-Nichi Institute of Technology. Faculty of Information Technology
Email :
sarayut.n@tni.ac.th
Name: Annop Monsakul
Organization :
Panyapiwat Institute of Management
Email :
annopmon@pim.ac.th
keyword:
Predictive maintenance
LCSH:
Machine learning
LCSH:
Quality control
-- Data processing
Abstract:
Thailand is a major hub for hard disk drive (HDD) manufacturing, where maintaining high equipment reliability is essential for product quality and export readiness. Critical testing machines, such as the Guzik Signal Analyzer (GSA 6000 Series) and the Read-Write Analyzer (4000 TDMR Series), can experience performance issues over time due to environmental changes and prolonged use. This paper presents a predictive maintenance (PdM) framework using ensemble machine learning models to predict equipment failures based on sensor data, particularly temperature readings. There are 6 models such as XGBoost, LightGBM, AdaBoost, CatBoost, Gradient Boosting Tree, and Bagging were trained on a real dataset. The Synthetic Minority Oversampling Technique (SMOTE) was used to handle class imbalance. Among all models, XGBoost achieved the best performance with 98.91 percent accuracy, 98.91 percent precision, 98.91 percent recall, F1-score 98.91 percent and an AUC of 0.9995. The proposed PdM system enables early fault detection, reduces unplanned downtime, and improves overall production efficiency.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2025
Modified:
2026-07-27
Issued:
2026-07-27
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Thailand Section (Computer Chapter) and the Department of Computer Science, Faculty of Science, Chiang Mai University. The 22nd International Joint Conference on Computer Science and Software Engineering (JCSSE 2025) (pp.169-174). Chiang Mai : Chiang Mai University
eng
©copyrights King Mongkut's University of Technology North Bangkok
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0.043189 วินาที
Saisuda Nantalek
| Title | Contributor | Type |
|---|---|---|
| Predictive maintenance for motor-operated valves: A machine learning approach to torque-based fault detection
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Thapana Sitthilertpisarn;Saisuda Nantalek;Sarayut Nonsiri;Napaphat Vichaidis | บทความ/Article | |
| Comparative study of ensemble learning for predictive maintenance in hdd manufacturing
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Saisuda Nantalek;Sarayut Nonsiri;Annop Monsakul | บทความ/Article |
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| A machine learning algorithms for drug identification: enhancing medication safety in Thailand
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| Predictive maintenance for motor-operated valves: A machine learning approach to torque-based fault detection
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| Comparative study of ensemble learning for predictive maintenance in hdd manufacturing
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Saisuda Nantalek;Sarayut Nonsiri;Annop Monsakul | บทความ/Article |
Annop Monsakul
| Title | Contributor | Type |
|---|---|---|
| Comparative study of ensemble learning for predictive maintenance in hdd manufacturing
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Saisuda Nantalek;Sarayut Nonsiri;Annop Monsakul | บทความ/Article |