- Data Collection: Sensors on machines continuously gather data such as temperature, vibrations, noises, and performance.
- Data Analysis: The collected data is analyzed using machine learning algorithms to detect patterns and anomalies.
- Prediction: The analysis predicts when a machine is likely to require maintenance before a breakdown occurs.
- Proactive Maintenance: Based on these predictions, maintenance can be planned and performed before costly failures or damages occur.
Benefits:
– Reduced Downtime: Machines operate more reliably as maintenance is performed in a timely manner.
– Cost Savings: Lower repair costs and more efficient resource utilization.
– Extended Machine Lifespan: Regular, need-based maintenance extends the operational life.
– Optimized Operations: Fewer unexpected disruptions lead to more efficient production.
Predictive Maintenance enables companies to plan maintenance more effectively and increase operational reliability.
