Digital twin for process simulation in SCADA systems - Step-by-Step Execution

Process Flow - Digital twin for process simulation

Start: Physical Process

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Sensors collect data

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Data sent to Digital Twin

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Digital Twin simulates process

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Simulation results analyzed

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Adjustments sent to Physical Process

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Physical Process updated

↩Loop back to Sensors collect data

The physical process is monitored by sensors that send data to the digital twin, which simulates and analyzes the process, then suggests adjustments back to the physical system.

Execution Sample

SCADA systems

1. Read sensor data
2. Update digital twin model
3. Run simulation step
4. Analyze output
5. Send control commands

This sequence shows how sensor data updates the digital twin, which simulates the process and sends control commands back.

Process Table

Step	Action	Input Data	Simulation State	Output/Command
1	Read sensor data	Temperature=75, Pressure=30	Model initialized	Data received
2	Update digital twin model	Sensor data	Model updated with new values	Ready to simulate
3	Run simulation step	Updated model	Simulated process state: Temp=76, Pressure=29.5	Simulation complete
4	Analyze output	Simulation results	Analysis done: Pressure slightly low	Adjustment needed
5	Send control commands	Adjustment decision	Commands sent to actuators	Physical process adjusted
6	Loop back	New sensor data expected	Waiting for next cycle	Cycle complete

💡 Cycle ends after sending control commands; process repeats continuously for real-time simulation.

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	Final
Temperature	N/A	75	75	76	76	76	Waiting new data
Pressure	N/A	30	30	29.5	29.5	29.5	Waiting new data
Simulation State	Idle	Idle	Updated	Simulated	Analyzed	Commands sent	Idle
Output/Command	None	None	None	None	Adjustment needed	Control signals sent	None

Key Moments - 3 Insights

Why does the simulation state change after reading sensor data?

Because the digital twin updates its model with the new sensor data (see execution_table step 2), preparing for accurate simulation.

Why is the pressure value slightly different in the simulation step?

The simulation predicts process behavior, so pressure changes from 30 to 29.5 to reflect expected real-world dynamics (execution_table step 3).

How does the digital twin influence the physical process?

It sends control commands based on simulation analysis to adjust the physical process (execution_table step 5), closing the feedback loop.

Visual Quiz - 3 Questions

Look at the execution table, what is the simulation state after step 3?

A Model updated with new values

B Simulated process state: Temp=76, Pressure=29.5

C Analysis done: Pressure slightly low

D Commands sent to actuators

💡 Hint

Check the 'Simulation State' column in execution_table at step 3.

At which step does the digital twin send control commands to the physical process?

A Step 2

B Step 3

C Step 5

D Step 6

💡 Hint

Look for 'Commands sent to actuators' in the Output/Command column.

If sensor data showed a pressure of 35 instead of 30, how would the simulation state after step 3 change?

A Simulated pressure would likely be higher than 29.5

B Simulated pressure would remain 29.5

C Simulation would not run

D Temperature would drop to 70

💡 Hint

Simulation state depends on input sensor data; see variable_tracker for pressure changes.

Concept Snapshot

Digital Twin for Process Simulation:
- Collect real-time sensor data
- Update virtual model with data
- Run simulation to predict process
- Analyze simulation output
- Send control commands to adjust process
- Repeat cycle continuously for real-time control

Full Transcript

A digital twin is a virtual copy of a physical process. Sensors collect data like temperature and pressure from the real process. This data updates the digital twin model. The twin runs a simulation step to predict how the process behaves. It analyzes the results and decides if adjustments are needed. Then it sends control commands back to the physical process to keep it running well. This cycle repeats continuously, allowing real-time monitoring and control.