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Manufacturing Event Simulator

This event simulator generates realistic manufacturing events for each asset in your assets.csv file and sends them to an Azure Event Hub to be ingested into the RTI workspace in Fabric.

Access Requirement

If you are the owner of the Azure Event Hub deployed with the solution, you already have required access to run this event simulator. If not, you will to be added as the Azure Event Hubs Data Sender role by the owner of the Event Hub or your Azure Admin.

Quick Start

1. Set Environment Variables

NOTE: If the executing environment deployed the resources via AZD following the deployment guide in this solution, the required environment variables for the event simulator will be set automatically and this step can be skipped.

If using Powershell, use this syntax for setting environment variables.

Visit the Azure Portal to get the Event Hub name and connection string of the environment.

export EVENT_HUB_CONNECTION_STRING="Endpoint=sb://..."
export EVENT_HUB_NAME="<event-hub-name>"

2. Set Environment Variables (Optional)

export SIMULATION_INTERVAL="5"        # Seconds between events per asset (default: 5)
export MAX_RUNTIME_SECONDS="300"      # Max runtime in seconds (default: unlimited)

3. Run the Simulator

cd src/simulator
# Basic usage (runs until Ctrl+C, quit, or q)
python event_simulator.py

# With custom interval (2 seconds between events)
python event_simulator.py --interval 2

# Run for specific duration (5 minutes)
python event_simulator.py --max-runtime 300

# Use custom data files
python event_simulator.py --assets-csv /path/to/assets.csv --products-csv /path/to/products.csv

Command Line Options

Option Description Default
--interval Seconds between events per asset 5.0
--max-runtime Maximum runtime in seconds Unlimited
--assets-csv Path to assets.csv file infra/data/assets.csv
--products-csv Path to products.csv file infra/data/products.csv

Interactive Runtime Controls

While the simulator is running, you can control it using these commands:

Command Aliases Description
anomaly [#] a [#] Switch to anomaly mode (all assets or specific asset #)
normal [#] n [#] Switch to normal mode (all assets or specific asset #)
status s Show current mode and statistics
stats Show detailed per-asset breakdown
help h, ? Show available commands
stop q Stop the simulation

Example Interactive Usage

# Start the simulator
python event_simulator.py --interval 2

# During runtime, type commands:
anomaly          # Switch ALL assets to anomaly mode
anomaly 2        # Switch only asset #2 to anomaly mode
normal 1         # Switch asset #1 back to normal mode
status           # Check current statistics (shows which assets are in which mode)
stats            # View per-asset breakdown with modes
normal           # Switch ALL assets back to normal mode
stop             # Stop simulation

Event Types

Normal Mode (Default)

  • Realistic operational sensor readings
  • Low defect probability (typically < 2%)
  • Values within normal operating ranges

Anomaly Mode

  • Extreme sensor readings indicating equipment issues
  • High defect probability (typically > 50%)
  • Simulates equipment failures and maintenance needs

How It Works

Asset Simulation

Each asset from assets.csv gets its own simulator thread that:

  1. Generates Random Event: Creates realistic readings based on asset type
  2. Calculates Defects: Uses sensor conditions to estimate defect probability
  3. Sends Events: Transmits events to Event Hub which will then stream to Eventstream in Fabric
  4. Responds to Mode Changes: Switches between normal and anomaly events

Usage Scenarios

Equipment Failure Testing - Single Asset

  1. Start simulation
  2. Use anomaly 2 to simulate equipment failure on asset #2 only
  3. Monitor your data pipeline's response to anomalous data from one asset
  4. Other assets continue generating normal events for comparison
  5. Use normal 2 to simulate repair completion

Equipment Failure Testing - All Assets

  1. Start simulation
  2. Use anomaly command to simulate widespread equipment issues
  3. Monitor system response to multiple failing assets
  4. Use normal to simulate all equipment returning to normal

Quality Control Validation

  • Use stats command to monitor defect rates per asset in real-time
  • Test alerting thresholds with targeted anomaly mode on specific assets
  • Validate quality control system responses