Improving Preventive Maintenance of Machinery Using Count Lifetime
Abstract
This project developed an integrated system that enabled equipment to autonomously count and monitor the service lifetime of internal machine components, thereby assessing their condition in real time and determining optimal maintenance intervals. By embedding this functionality into the equipment, the system facilitated proactive decision-making for maintenance activities before component failure occurs. Furthermore, a preventive maintenance system was designed, installed, and calibrated to automatically inspect, detect, and issue alerts when any component approached or exceeded its designated service lifespan. This predictive capability significantly reduced the likelihood of unexpected breakdowns, minimizes potential damage, and ultimately shortens machine downtime. The system was implemented and tested in a case study factory specializing in the production of electronic parts. Quantitative data were collected during both the pre-implementation period and after the system was fully operational. The comparison of these datasets allowed for an evaluation of the system's impact on production continuity and maintenance efficiency. This research, adopting a quantitative methodology,
enhanced preventive maintenance practices and improved overall manufacturing performance through more accurate and timely maintenance scheduling.
Keywords
References
- Chuaitakhu, R. & Jongkol, P. (2025). Improving preventive maintenance of machinery using count lifetime. The Eurasia Proceedings of Science, Technology, Engineering and Mathematics (EPSTEM), 35, 38-45.
Details
Primary Language
English
Subjects
Electrical Machines and Drives
Journal Section
Research Article
Early Pub Date
October 20, 2025
Publication Date
September 30, 2025
Submission Date
May 2, 2025
Acceptance Date
June 9, 2025
Published in Issue
Year 2025 Volume: 35