31. Applications in Predictive Maintenance
Predictive maintenance (PdM) uses advanced technologies such as robotics and data analytics to foresee equipment failures before they happen. This proactive approach, essential in civil engineering, enhances safety, optimizes maintenance, and extends the lifespan of infrastructure. The chapter explores the various roles of robotics, sensors, and IoT in PdM, presenting case studies and future trends that emphasize the integration of these technologies in smart cities and construction.
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What we have learnt
- Predictive maintenance leverages real-time data and historical patterns to prevent equipment failures.
- Robotics plays a crucial role in inspecting and maintaining civil infrastructure, enhancing safety and efficiency.
- Integration with IoT and data analytics enables continuous monitoring and automated maintenance scheduling.
Key Concepts
- -- Predictive Maintenance (PdM)
- A strategy that uses real-time data to predict equipment failures before they occur.
- -- Condition Monitoring
- The continuous gathering of real-time data from sensors to assess the health of mechanical systems.
- -- Digital Twin
- A virtual representation of physical infrastructure that is updated in real-time using sensor data.
- -- Machine Learning
- Applications of algorithms to detect trends and anomalies in data gathered from various sources.
- -- Robotics
- The use of robots to perform tasks that are hazardous, precision-requiring, or difficult to access.
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