Machine learning-driven condition monitoring and fault detection in manufacturing

Mahmoud, Amena and Talpur, Kazim Raza and Shah, Asadullah and Saini, Shilpa and Juneja, Sapna and Elbelkasy, Manal Sobhy Ali (2025) Machine learning-driven condition monitoring and fault detection in manufacturing. In: 9th International Conference on Engineering Technologies and Applied Sciences (ICETAS2024), 25th August 2025, Bahrain.

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Abstract

The manufacturing industry has witnessed a surge in the adoption of machine learning (ML) techniques to enhance various aspects of production processes. One critical application of ML in manufacturing is condition monitoring and fault detection, which play a pivotal role in ensuring product quality, minimizing downtime, and maximizing operational efficiency. This paper presents a comprehensive review of the use of machine learning for condition monitoring and fault detection in manufacturing environments. It also discusses the importance of data preprocessing, feature engineering, and model selection in developing robust and reliable ML-based condition monitoring systems. Furthermore, the paper addresses the case studies, challenges and future trends associated with deploying ML-driven condition monitoring, such as data quality, model interpretability, and integration with existing manufacturing systems. It also highlights emerging trends and future research directions in this domain, including the integration of edge computing, digital twins, and advanced analytics for real-time, predictive, and prescriptive maintenance strategies.

Item Type:	Proceeding Paper (Other)
Additional Information:	6566/123209
Uncontrolled Keywords:	Condition Monitoring; Fault Detection; Machine Learning; Supervised Learning, Sensor- based Monitoring
Subjects:	T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Prof Asadullah Shah
Date Deposited:	17 Sep 2025 15:03
Last Modified:	17 Sep 2025 16:01
URI:	http://irep.iium.edu.my/id/eprint/123209

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