⛏️ Mining, Metals & Chemicals · Data Flow
Predictive Maintenance for Heavy Equipment
How sensor data from crushers, conveyors and mills predicts failures before they happen, turning into maintenance work orders.
Drawing diagram…
What this diagram shows
- Vibration and temperature trends show wear early
- A model estimates remaining useful life
- Work orders are raised automatically in the maintenance system
Prompt used
Predictive maintenance data flow: vibration, temperature and oil sensors on crushers, conveyors and mills send data through edge gateways to a time-series database. Condition monitoring software computes features. A model predicts remaining useful life and failure risk. High-risk alerts create work orders in the maintenance system (SAP PM), which checks spare parts stock.
Mermaid code
flowchart LR VIB[Vibration Sensors] -->|Readings| EG[Edge Gateways] TMP[Temperature Sensors] -->|Readings| EG OIL[Oil Quality Sensors] -->|Readings| EG EG -->|Filtered data| TSDB[(Time-series DB)] TSDB -->|Signals| CM[Condition Monitoring] CM -->|Features| PM[Failure Prediction Model] HIST[(Failure History)] -->|Training data| PM PM -->|High risk, remaining life| WO[Work Order in Maintenance System] INV[(Spare Parts Stock)] -->|Availability| WO WO -->|Schedule| CREW[Maintenance Crew]
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