Integrate data from IOT and SCADA systems

What makes us IOT experts?

A core part of the work we do at our parent company is to collect, organise, and analyse large amounts of industrial data. We collect 50+ billion data points every single day and work at a petabyte scale. This data comes from a variety of SCADA and IOT sources and is used to manage assets worth billions of dollars.

Rest assured, we know a thing or two how to handle data - the variety, volume, and velocity of it.

Two things form the the foundation for any 'Predictive Maintenance' strategy.

1. Reliable Data Collection.

2. Predictive Maintenance Rules.

Handling the DATA MONSTER.

The straightforward way to is to log data originating from any of your IOT sensors and SCADA systems and use our super simple API to update assets and work orders.

A few examples of what you can achieve are ....

• Update 'counters' belonging to assets.

• Generate a work order every time a counter hits a certain level.

• Generate work order when any IOT throws up an 'Alarm'.

As usual the devil is in the details ....

• SCADA systems trip all the time.

• Counters jump and give meaningless readings.

• Time stamps are messy.

• Time zones are messier.

• Let's not talk about day light savings.

• Network is choppy. Data arrives late.

We've encountered almost all edge cases and then some more when working with edge devices and we know how to deal with this monster.

Rules Engine

We've built a rules engine that can parse SCADA data, apply your business logic and then decide how to update assets or generate work orders.

Data Warehousing

We can go a step further and collect your industrial data and warehouse it - even if its petabyte scale. Data comes in all shapes and sizes and our back-end systems can scale to match your data flow.

• Variety - XML, CSV, Tag Data, Alarms, Quality - we handle it all.

• Volume - Billions of data points - our storage scales.

• Velocity - Real time data hose - no problem.

Data can get unwieldy and overwhelming quite fast. We work with your teams to make your data work for you. Not the other way round.

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.

Note

Integrating IOT and SCADA systems and data warehousing are part of the Mission Critical and Enterprise Plans. These require an API integration. Please get in touch to understand these options better.

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