What is the role of trend data analysis in maintenance planning?

• A. Predict weather patterns.
• B. Create energy models.
• C. Detect drifts and validate sustained performance.
• D. Determine staffing levels.

Answer: (C)

Trend data analysis in maintenance planning focuses on monitoring how equipment performance changes over time to catch gradual degradation before failures occur. By collecting and reviewing time-series data—such as energy use, temperature and pressure readings, fault codes, run hours, and sensor calibrations—you establish a baseline and look for drift from that baseline. When a drift is detected, maintenance actions can be scheduled to address wear, fouling, sensor drift, or control calibration, helping to sustain performance and avoid unexpected downtime. It also serves to verify that previous maintenance and calibrations have produced the intended results, supporting ongoing commissioning and ensuring systems continue meeting design and energy targets. While weather prediction, energy modeling, or staffing decisions are valuable in their own right, trend data analysis for maintenance is about identifying and validating sustained performance over time.