Abstract
This study addresses the problem of low equipment availability in plastic manufacturing industries, which limits productivity and efficiency. A technical diagnosis identified critical failure modes in the extrusion screw, bearings, and control panel. Validation through Arena simulation showed a 128.60% increase in MTBF and a 2.07% improvement in availability, while MTTR remained at 59.67 hours. To solve this problem, the research proposes a hybrid maintenance approach that integrates Preventive Maintenance based on optimal intervention intervals calculated using the Weibull distribution, and Predictive Maintenance using a system based on a neural network with persistent memory for temperature data. According to the results, integrating preventive and predictive maintenance reduces unplanned downtimes and improves equipment availability in industrial operations.
| Original language | English |
|---|---|
| Title of host publication | 2025 11th International Conference on Innovation and Trends in Engineering, CONIITI 2025 - Conference Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Edition | 2025 |
| ISBN (Electronic) | 9798331591328 |
| DOIs | |
| State | Published - 2025 |
| Event | 11th International Conference on Innovation and Trends in Engineering, CONIITI 2025 - Bogota, Colombia Duration: 1 Oct 2025 → 3 Oct 2025 |
Conference
| Conference | 11th International Conference on Innovation and Trends in Engineering, CONIITI 2025 |
|---|---|
| Country/Territory | Colombia |
| City | Bogota |
| Period | 1/10/25 → 3/10/25 |
Keywords
- Availability
- LSTM
- Predictive Maintenance
- Preventive Maintenance
- Simulation
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