Manuscript Title:

OPTIMIZING PREDICTIVE MAINTENANCE IN MINING: HARNESSING INDUSTRY 4.0 TECHNOLOGIES

Author:

DOAA AHMAD ALQARALEH, HASSAN MOHAMED, SAMI HAJJAJ, RADZI ARIDI

DOI Number:

DOI:10.5281/zenodo.14910110

Published : 2025-02-23

About the author(s)

1. DOAA AHMAD ALQARALEH - Centre for Advanced Mechatronics and Robotics (CaMaRo), Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia. Institute of Informatics and Computing in Energy (IICE), Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia.
2. HASSAN MOHAMED - Centre for Advanced Mechatronics and Robotics (CaMaRo), Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia. Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia.
3. SAMI HAJJAJ - Department of Smart Computing and Cyber Resilience School of Engineering and Technology (SET), Sunway University.
4. RADZI ARIDI - Institute of Informatics and Computing in Energy (IICE), Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia.

Full Text : PDF

Abstract

Despite the great volumes of work being produced in the sense of capitalizing on the fourth industrial revolution technologies to apply predictive maintenance in the manufacturing industry, there is a lack of research concerning the integration of Industry 4.0 technologies. This study attempts to do this by examining both the trends and the challenges of the application of stances upon Industry 4.0 and the PdM in mine. The main results show that the use of data is embraced as an essential part of the Industry 4.0 implementation processes in predictive maintenance. Moreover, these situations contradict each other, i.e. trends and challenges differ in the traditional environment in comparison to some difficult environments. Use of these codes, during PdM practice, will enable a practitioner to know what to expect and serve as a foundation for further research. The Industry 4.0 era holds enormous capacity for the enhancement of industrial process efficiency, mainly where preventive maintenance is a key consideration. The Internet of Things (IoT), which is interconnected and decentralized in Industry 4.0, makes it possible to get any kind of data without location or time dependency and optimize maintenance schedules. Placing a significant focus on these features facilitates condition-based maintenance, improvement of maintenance as appropriate, and time-condition-based maintenance when necessary.


Keywords

Industry 4.0; Predictive Maintenance (PdM); Manufacturing Industry; Mining Sector; Artificial Intelligence (AI); Condition Monitoring.