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In Situ Surface Temperature Measurement in a Conveyor Belt Furnace via Inline Infrared Thermography
Published on: May 30, 2020
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Sensor-Based Diagnostics for Conveyor Belt Condition Monitoring and Predictive Refurbishment
Ryszard Błażej1, Leszek Jurdziak1, Aleksandra Rzeszowska1
1Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15 St., 50-421 Wrocław, Poland.
Sensors (Basel, Switzerland)
|September 19, 2025
Summary
Condition-based maintenance (CBM) using in situ diagnostics improved conveyor belt refurbishment success rates from 70% to over 90%. This sensor-based approach optimizes lifecycle management, reduces costs, and supports the circular economy.
Area of Science:
- Mining Engineering
- Materials Science
- Industrial Maintenance
Background:
- Rising raw material costs and complex supply chains impact conveyor belt durability and availability.
- Traditional visual inspections for conveyor belt maintenance are subjective and less effective.
- Condition-based maintenance (CBM) with in situ diagnostics is crucial for modern industrial operations.
Purpose of the Study:
- To demonstrate the effectiveness of sensor-based diagnostics in replacing subjective visual inspections for conveyor belt maintenance.
- To optimize conveyor belt lifecycle management and refurbishment decision-making.
- To highlight the benefits of predictive maintenance for industrial conveyor systems.
Main Methods:
- Implemented objective, repeatable measurements of belt core condition and thickness using inductive and ultrasonic technologies.
- Shifted refurbishment decisions from a general plant level to a conveyor-specific approach.
- Utilized real-time, sensor-based monitoring for in situ diagnostics.
Main Results:
- Conveyor belt refurbishment success rates improved from 70% to over 90%.
- Optimized belt lifecycle management, leading to increased belt reuse and extended core life.
- Enabled predictive maintenance, reducing premature or delayed replacements and lowering overall costs.
Conclusions:
- Sensor-based diagnostics provide objective data for effective conveyor belt maintenance.
- Predictive maintenance strategies significantly enhance operational efficiency and cost-effectiveness.
- This approach supports the circular economy by maximizing resource utilization and minimizing waste in industrial settings.
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