Abstract
Human resource in maintenance remains a challenge in the overall business labor budget, labor costs, and the management thereof. This study aims to develop a model for maintenance management which fosters an optimum human resource in maintenance. The study uses system dynamics modeling to determine the maintenance management system's behavior. The 4IR technologies are integrated into this model and simulations are conducted to determine the 4IR technologies' impact analysis using descriptive statistics. Post these simulations, the results revealed that the implementation of 4IR technologies yields an overall gain in maintenance human resource optimization by 27.46% gain when compared to a similar system of maintenance management without the 4IR technologies' deployment. Another benefit of the 4IR technologies deployment is analyzed using standard deviation and found to foster a predictive maintenance strategy. This study concludes that the predictive maintenance strategy intensifies the optimization of the overall human resource in maintenance.
Original language | English |
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Pages (from-to) | 1900-1908 |
Number of pages | 9 |
Journal | Procedia Computer Science |
Volume | 232 |
DOIs | |
Publication status | Published - 2024 |
Externally published | Yes |
Event | 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 - Lisbon, Portugal Duration: 22 Nov 2023 → 24 Nov 2023 |
Keywords
- Digital Technologies
- Human resources optimization
- Maintenance Labour
- Optimal maintenance execution
ASJC Scopus subject areas
- General Computer Science