What is a Predictive Maintenance?

Data and Predictive Maintenance.

• predict /prɪˈdɪkt/
  verb
  to say that an event or action will happen in the future, especially as a result of knowledge or experience

Predictive Maintenance is the art and science of foreseeing - with reasonable accuracy - how a machine will behave in the near future.

Let's say you have a car. The car manufacturer will recommend you get the car serviced after every 10,000 kms (or miles) even if the car is visibly running fine. It's generally expected that after 10,000 kms a few nuts and bolts might have come loose. If left unchecked, this might result in a minor or major catastrophe. So you send the car to the garage and a mechanic does a bumper-to-bumper inspection. He tightens some loose bolts, changes a fuel filter, tops up some blinker fluid, and gives you back your car after a day or two.

Your car is now in a better condition than before and you can drive assured that there are going to be no unexpected breakdowns. All in all you lose access to your car for a day or two and you pay a small price to the garage. This is called 'Preventive Maintenance (PM)'. The reason you do PM is to avoid catastrophic breakdowns at unexpected times which can turn out to be very very expensive.

Machines breakdown even after they undergo regular Preventive Maintenance due to a thing called Murphy's law ¯\_(ツ)_/¯. Unexpected breakdowns cause huge mental and financial stress to humans and organisations. That's why we have Predictive Maintenance (PdM).

Let's continue with the 'Car' analogy. Predictive Maintenance needs data. All modern cars come with some built in sensors that collect data on a continual basis. We can collect this data and analyse it in real or near-real time. Let's say there's a sensor that tracks engine temperature. We know from experience that the engine temperature must be within an optimal range of 90°C and 105°C. We can create a rule which raises an alert "If engine temperature > 105°C for >= 10 mins".

Now instead of waiting for the next Preventive Maintenance schedule to kick in, we can send the car to the garage and get is repaired immediately. This, in short, is Predictive Maintenance.

Predictive Maintenance is widely used across industries, including manufacturing, oil and gas, healthcare, transportation, facilities/building management, hotels, etc., to ensure asset reliability and operational continuity.

Handling Predictive Maintenance with CMMS.

A Computerized Maintenance Management System (CMMS) is a special software designed to streamline maintenance operations. A CMMS will involve few or all of the following ....

Scheduling and Planning

CMMS software allows maintenance managers to create detailed schedules for maintenance tasks. These schedules can be based on time, usage, or condition. To illustrate ....

• Monthly inspections of HVAC systems.

• Machine Lubrication after every 400 hours of operation.

• Sensor Calibration based on real-time performance data.

Automated Work Orders

A CMMS software automatically generates work orders based on time, usage or conditions and assigns them to the correct technician. Regular reminders (email, push notifications, text messages) ensure that every maintenance task is attended to.

Asset Tracking

A good CMMS software can maintain a complete database of all assets, sub-assets, and parts, including their maintenance history and warranty information. This ensures that every asset gets the care it needs, when it needs.

Condition Based Maintenance

Advanced CMMS platforms like SuperCMMS analyse data from IoT sensors and SCADA systems in real time to monitor equipment health. For example, vibration sensors can detect abnormalities in a machine and trigger a work order for preventive maintenance before a major failure occurs.

Resource Optimization

A critical part of preventive maintenance is to allocate resources (time, labor, tools, parts) efficiently. This also involves tracking inventory levels and ensuring that spare parts are available when needed. This helps in reducing downtime and minimizing costs.

Reporting and Analytics

Data drives everything. CMMS software can provide detailed reports on maintenance activities, like ....

• MTTR and MTBF reports

• Audit compliance for legal reporting.

• Bill of materials (BoM).

• Real time equipment uptime metrics.

These insights help in 'data-driven' decision making and continuous improvements.

Predictive Maintenance Rules.

The 'Rules Engine' is a proprietary module within SuperCMMS that is built on a solid foundation of mathematical and statistical machine learning models. It scans your incoming data in real or near-real time, checks for anomalies and generates work orders.

Some of the rules you can define are ....

1. Threshold Exceeded (Instant Trigger): Triggered when a value crosses a defined limit.

📌 Example Scenarios:

• Temperature > 100°C → Shut down the machine.

• Oil pressure < 20 PSI → Send an alert.

• Vibration > 8 mm/s → Create a work order.

• Battery voltage < 10V → Notify maintenance team.

2. State Change (Boolean Triggers): Triggered when a boolean (True/False) value changes.

📌 Example Scenarios:

• Door Open = True → Send security alert.

• Smoke Detector = True → Activate fire suppression.

• Machine Fault = True → Log an error event.

• Conveyor Jammed = True → Stop the entire line.

3. Rate of Change (Sudden Increases or Decreases): Triggered when a value changes too quickly over a time window.

📌 Example Scenarios:

• Tank level drops by 20% in 5 min → Possible leak detected.

• Pressure increases by 30 PSI in 2 min → Potential blockage.

• Temperature rises by 10°C in 1 min → Risk of overheating.

• RPM drops by 50% within 30 sec → Motor failure risk.

4. Time-Based Events (Sustained Condition Triggers): Triggered when a condition stays active for a set time.

📌 Example Scenarios:

• Vibration > 5 mm/s for 10 min → Create work order.

• Coolant temperature > 90°C for 30 min → Shutdown system.

• Humidity > 70% for 2 hours → Turn on dehumidifier.

• Light level < 10 Lux for 1 hour → Check for lighting failure.

5. Consecutive Occurrences (Pattern-Based Rules): Triggered when a condition happens multiple times in a row.

📌 Example Scenarios:

• 3 consecutive high-pressure spikes in 5 min → Possible blockage.

• 5 failed sensor readings in a row → Replace sensor.

• 3 power surges within 10 min → Investigate electrical fault.

• 4 conveyor belt stoppages in 1 hour → Create a work order.

6. Value In Range for a Set Time (Window Condition): Triggered when a value stays within a certain range for too long.

📌 Example Scenarios:

• Temperature between 80°C and 90°C for 15 min → Cooling issue.

• Pressure between 50 PSI and 60 PSI for 30 min → Investigate for clogging.

• Machine idle time between 5-10 min for 3 cycles → Possible efficiency issue.

• Humidity between 40% and 50% for 2 hours → Check climate control system.

7. Combination Rules (Multiple Conditions Met): Triggered when two or more conditions occur together.

📌 Example Scenarios:

• (Temperature > 100°C) AND (Pressure > 200 PSI) → Emergency shutdown.

• (Oil level < 10%) OR (Engine running) → Low lubrication warning.

• (Humidity > 80%) AND (Fan speed = 0) → HVAC failure alert.

• (Voltage drop > 20V) AND (Power Load > 80%) → Possible overload.

You can define a combination of rules and automatically generate alerts and work orders for predictive maintenance whenever these rules are met.

Need More?

As part of the 'Enterprise Plan', SuperCMMS can help you in ....

• collecting data from your IOT and/or SCADA systems,

• warehousing this data in central cloud servers, and

• designing a predictive maintenance strategy.

SuperCMMS makes Predictive Maintenance easy.

SuperCMMS is a 'Computerized Maintenance Management System (CMMS)' that brings together 'Asset Management', 'Work Order Management', and 'Inventory Management' in one seamless platform. It is available in the Cloud and can be accessed both on Web and Mobile (iPhone, Android).

SuperCMMS is free for 5 team members - forever and all features included. The paid version will save you a ton of money compared to ANY alternative on the market.

Give it a try. Your team, especially the field staff, will love you for it.

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