2.1 Reactive Maintenance

This is the simplest method: repair only when something breaks down.

Characteristics:

·        No prior planning

·        Intervention only after equipment has failed

Advantages:

·        No initial investment cost

·        Maximizes the service life of components

Disadvantages:

·        Causes unexpected downtime

·        High emergency repair costs

·        Difficult to control operations

Suitable for:

·        Auxiliary equipment

·        Low-value machinery that is easy to replace

2.2 Preventive Maintenance

This method is based on a scheduled maintenance plan.

Examples:

Changing oil after every 3,000 operating hours
Inspecting equipment monthly

Advantages:

·        Reduces unexpected failures

·        Makes workforce planning easier

Disadvantages:

·        May lead to “excessive” maintenance

·        Can be costly if the schedule is not optimized

Suitable for:

·        Standard equipment

·        Machinery that wears out over time

2.3 Preactive Maintenance

This is an upgraded step from preventive maintenance, focusing on optimizing operating conditions from the beginning.

Examples:

·        Ensuring lubrication meets required standards

·        Keeping the operating environment clean and stable

Advantages:

·        Reduces failures from the root

·        Low cost with long-term effectiveness

Disadvantages:

Results may not be immediately visible

Suitable for:

·        Continuous production lines

·        Machinery requiring high operational stability

2.4 Predictive Maintenance

This is a modern method based on data and the actual condition of equipment.

How it works:

Uses sensors to measure vibration, temperature, and pressure
Analyzes data to predict failures

Advantages:

·        Maintenance is performed only when necessary

·        Minimizes downtime

·        Optimizes spare parts and material costs

Disadvantages:

·        High initial investment

·        Requires a data system and technical expertise

Suitable for:

·        Critical assets

·        Production lines with high downtime costs

2.5 Proactive Maintenance

Unlike the methods above, this approach focuses on:

ð Identifying and eliminating the root causes of failures

Examples:

·        Improving machine design

·        Optimizing operating processes

Advantages:

·         Increases long-term reliability

·         Reduces recurring failures

Disadvantages:

·        Requires a change in mindset and systems

·        Requires in-depth analysis

Suitable for:

·        Large-scale manufacturing enterprises

·        Complex systems

Comparison Table of Equipment Maintenance Strategies

Criteria	Reactive Maintenance	Preventive Maintenance	Preactive Maintenance	Predictive Maintenance	Proactive Maintenance
Nature	Passive	Periodic	Operational optimization	Data-driven	Strategic
Investment cost	Low	Medium	Low	High	Very high
Long-term effectiveness	Low	Medium	Good	Very good	Excellent
Downtime	High	Medium	Low	Very low	Lowest

3. Trends in Equipment Maintenance Management: AI and Data-Driven Maintenance

In recent years, the application of AI in equipment maintenance has become an inevitable trend.

3.1 From Traditional Maintenance to Data-Driven Maintenance

In the past:

·        Decisions were based on experience

·        Businesses reacted after failures occurred

Today:

·        Decisions are based on real-time data

·        Risks are predicted in advance

=> This is called Data-driven Maintenance.

3.2 AI in Predictive Maintenance

AI helps elevate predictive maintenance to a new level.

AI capabilities include:

·        Analyzing historical data

·        Detecting anomalies

·        Predicting equipment lifespan, also known as RUL — Remaining Useful Life

Benefits:

·        Reduces downtime by 30–70%

·        Optimizes maintenance schedules

·        Reduces operating costs

3.3 AI Support for Troubleshooting

One of the most practical applications is:

=> AI helps technicians resolve faults faster.

Example:

The machine vibrates abnormally → The system suggests possible causes:

·        Shaft misalignment

·        Bearing wear

·        Imbalance

Benefits:

·        Shortens repair time

·        Reduces dependence on experts

·        Standardizes troubleshooting processes

3.4 AI Assistants in CMMS Systems

Today, many CMMS systems — Computerized Maintenance Management Systems — have integrated AI to:

·        Look up repair history

·        Suggest handling methods

·        Quickly find technical documents

=> Technicians only need to “ask the system” instead of searching manually.

3.5 Automated Maintenance Planning

AI can:

·        Recommend optimal maintenance schedules

·        Allocate manpower

·        Forecast spare parts and material demand

=>  This helps businesses shift from:

Manual planning → to automated optimization.

4. Core Technologies for Smart Maintenance

To implement smart maintenance effectively, businesses often combine:

·        IoT sensors for equipment monitoring

·        CMMS/EAM systems

·        Cloud and Big Data

·        AI/Machine Learning

·        Mobile apps for technicians

=>  Together, these create a modern maintenance management ecosystem.

5. How Should Businesses Apply Maintenance Strategies?

There is no single method that fits all cases.

Recommended strategy:

·        Critical equipment: Predictive Maintenance + AI

·        Standard equipment: Preventive Maintenance

·        Auxiliary equipment: Reactive Maintenance

·        Entire system: Move toward Proactive Maintenance

6. Roadmap for Implementing Smart Maintenance in Enterprises

To achieve successful transformation, businesses should follow four stages:

Stage 1 — Digitization: Apply CMMS software to manage equipment lists and equipment history.

Stage 2 — Standardization: Build standardized preventive maintenance processes.

Stage 3 — Connectivity: Install IoT sensors to collect real-time data.

Stage 4 — Intelligence: Apply AI to analyze data and support automated decision-making.

Conclusion

The difference between a factory that operates smoothly and one that is constantly “putting out fires” does not lie in the quality of its equipment, but in its maintenance strategy.

Leading businesses do not wait for machines to break down before repairing them. They take control by:

·        Predicting risks instead of reacting to failures

·        Optimizing based on data instead of intuition

·        Applying AI and IoT to automate processes\

The application of technology and AI is no longer optional. It has become a mandatory requirement for businesses to break through and lead in the era of smart manufacturing.

Are you looking for an optimal maintenance solution for your factory? Contact Vietsoft experts at 0986 778 578 for a consultation on an AI-integrated CMMS implementation roadmap today.