Preventive vs Predictive Maintenance: Which Strategy Fits Your Equipment?

Unplanned equipment failures stop production, damage products, create safety risks and often cost far more to fix than planned work. Choosing the right maintenance strategy for each machine is one of the most effective ways to improve reliability. There is no single best approach; the right answer depends on how the equipment fails and what a failure costs.

The four main strategies

1. Reactive (run-to-failure)

Fix equipment only when it breaks. This is a legitimate choice for inexpensive, non-critical items where failure is harmless and replacement is quick, such as a spare light fitting. It is a poor choice for critical production equipment.

2. Preventive (time- or usage-based)

Perform maintenance at fixed intervals: every month, every 500 operating hours, every 10,000 cycles. Typical tasks include lubrication, filter changes, inspections, adjustments and replacing wear parts.

• Strengths: simple to plan; effective for failures that clearly relate to age or usage.
• Weaknesses: parts may be replaced while still healthy, and failures that occur randomly between intervals are not prevented.

3. Condition-based

Monitor indicators of equipment health and act when they cross a threshold: a vibration level, a temperature, a pressure drop across a filter.

4. Predictive

Use trends in condition data, often with analytics, to forecast when a failure is likely and schedule work just before it. Predictive maintenance is condition-based maintenance taken further, with a focus on forecasting.

Common condition monitoring techniques

• Vibration analysis: detects imbalance, misalignment, looseness and bearing wear in rotating equipment.
• Infrared thermography: finds hot spots in electrical panels, motors and bearings.
• Oil analysis: reveals wear particles, contamination and lubricant degradation.
• Ultrasonic detection: finds compressed air and steam leaks and early bearing problems.
• Motor current analysis: identifies electrical and mechanical issues in motors.
• Process data: pressure, flow, temperature and power trends from existing control systems.

How to choose for each asset

1. List and rank assets by criticality: consider safety, environmental impact, production loss, repair cost and lead time for spares.
2. Understand how each asset fails. Does it wear out predictably with use, or fail randomly? Does it show warning signs before failure?
3. Match the strategy:
   • Low criticality, cheap to replace: reactive may be fine.
   • Predictable wear: preventive maintenance at sensible intervals.
   • Critical equipment with detectable warning signs: condition-based or predictive.
4. Review using real data. Adjust intervals and thresholds based on what failures actually occur.

Lubrication: the foundation

Many mechanical failures trace back to lubrication: the wrong lubricant, too much, too little, or contamination. A clear lubrication schedule, correctly specified lubricants and clean storage are among the cheapest reliability improvements available.

Use a maintenance management system

A computerised maintenance management system (CMMS) schedules tasks, records work and parts used, and builds the history you need to improve. Even a well-organised spreadsheet is better than memory. Track simple measures such as planned versus unplanned work, mean time between failures and downtime by cause.

Measure the impact

Maintenance improvements should show up in equipment availability. Overall Equipment Effectiveness combines availability with performance and quality; see how to calculate OEE. And never perform maintenance on energised equipment without proper isolation; read our guide to lockout/tagout basics.