Preventive Maintenance

                                                                PREVENTIVE MAINTENANCE

What is Preventive Maintenance?

Preventive maintenance (PM) is a proactive maintenance strategy that involves regularly scheduled inspections, servicing, and repairs of equipment to prevent unexpected failures and extend its lifespan. It includes tasks like lubrication, cleaning, calibration, part replacements, and performance checks. The goal is to reduce downtime, improve efficiency, and minimize costly emergency repairs.

PM is divided into different types. They are

1. Usage Based Maintenance 
2. Time Based Maintenance 
3. Condition Based Maintenance 
4. Predictive Maintenance 
5. Prescriptive Maintenance 

Let's go through each of the above-mentioned types one by one.

1. Usage Based Maintenance (UBM)

          UBM is a preventive maintenance strategy where servicing is scheduled based on equipment usage, such as operating hours, cycles, or mileage. It ensures maintenance occurs at the right time to prevent failures

        

 Examples

•  Fleet Vehicles: In a delivery company, oil changes and tire rotations are performed on trucks every 10,000 kilometers. This usage-based approach ensures vehicles operate efficiently and reduces the risk of breakdowns.

•  Industrial Pumps: A chemical processing plant schedules maintenance for pumps after every 2,000 hours of operation. This includes inspecting seals, checking for leaks, and cleaning filters, ensuring continuous and safe operation.

2. Time Based Maintenance (TBM)

           TBM is a preventive maintenance strategy where servicing is scheduled at fixed time intervals, regardless of equipment condition. Tasks like lubrication, inspections, and part replacements are performed periodically to prevent failures.

Examples

• HVAC Systems: In a commercial building, air filters are replaced every 3 months as part of time-based maintenance to ensure proper airflow and air quality, regardless of filter condition.     

• Elevators: In a high-rise building, elevators undergo lubrication and safety checks every 6 months to maintain smooth operation and prevent unexpected breakdowns.

3. Condition Based Maintenance (CBM)

           CBM is a preventive maintenance strategy where maintenance is performed based on the actual condition of equipment, often determined through monitoring tools or sensors. It involves inspecting parameters like temperature, vibration, or pressure. Maintenance is done when readings indicate the need, preventing unnecessary servicing and reducing costs.

Examples

• Power Generators: In a power plant, vibration sensors and temperature monitoring on generator bearings are used to detect wear or overheating. Maintenance is performed when sensor data shows abnormal conditions, preventing unplanned downtime. 

•  Cooling Fans in Servers: In a data center, cooling fans are monitored for airflow and temperature. If the sensors detect reduced airflow or overheating, maintenance is triggered to clean or replace components, preventing system overheating.

4. Predictive Maintenance (PDM)

          PDM uses advanced data analytics and real-time monitoring to predict equipment failures before they occur. By analyzing patterns from sensors and historical data, it identifies potential issues early. This allows for targeted maintenance, reducing downtime, extending equipment life, and optimizing resource allocation, ultimately saving costs.

Examples

• Solar Panels: A solar power plant uses infrared cameras and performance monitoring systems to detect abnormal heat spots or performance degradation in solar panels. Predictive algorithms analyze the data, identifying potential failures, allowing for maintenance before a major breakdown occurs. 

• Uninterruptible Power Supplies (UPS): In a data center, predictive maintenance monitors battery voltage and charging cycles. By analyzing performance data, the system predicts battery failure before it happens, enabling replacement or servicing of batteries before they cause power disruptions.

5) Prescriptive Maintenance (RxM)

          RxM goes beyond predicting equipment failure by not only identifying potential issues but also recommending specific maintenance actions. It uses advanced analytics and machine learning to suggest the most effective repair methods, optimal timing, and resource allocation, enhancing decision-making and minimizing costs while improving equipment reliability.

Examples

• Power Grid Transformer Maintenance: A power company uses smart sensors to monitor transformers for temperature spikes, oil degradation, and load imbalances. The system detects an abnormal temperature rise and prescribes a coolant refill and load redistribution to prevent overheating and potential failure, ensuring uninterrupted power supply.

• Data Center UPS System Optimization: A data center monitors its Uninterruptible Power Supply (UPS) batteries using AI-driven diagnostics. The system detects a slow decline in battery charge retention and prescribes the replacement of specific battery cells before failure occurs, preventing downtime and ensuring continuous operation.