Enrich Data & Scripts (Tutorial)

What You'll Learn

• Write tag expressions
• Create script tasks
• Build script classes
• Use multiple languages (C#, VB.NET, Python)

Prerequisites

• Basic programming knowledge
• Tags configured in UNS

Step 1: Simple Tag Expressions

1. Navigate to Unified Namespace → Tags
2. Add calculated tag:

Temperature Conversion:

• Name: Tank1_TempF
• Expression: @Tag.Tank1_TempC * 9/5 + 32
• Type: Double
• Description: Temperature in Fahrenheit

Conditional Logic:

• Name: System_Status
• Expression: @Tag.Motor1_Running AND @Tag.Pump1_Running ? "Running" : "Stopped"
• Type: Text

Step 2: Create Script Task

1. Go to Scripts → Tasks
2. Add new task:

Production Counter:

csharp

// Reset counter at shift change
DateTime now = DateTime.Now;
if (now.Hour == 6 || now.Hour == 14 || now.Hour == 22)
{
    if (@Tag.ShiftReset == false)
    {
        @Tag.Units_Previous = @Tag.Units_Produced;
        @Tag.Units_Produced = 0;
        @Tag.ShiftReset = true;
    }
}
else
{
    @Tag.ShiftReset = false;
}

Configure:

• Trigger: Timer
• Rate: 60000ms (1 minute)
• Domain: Server

Step 3: Build Script Class

1. Navigate to Scripts → Classes
2. Create class:

TankCalculations:

csharp

public class TankCalculations
{
    public static double CalculateVolume(double level, double diameter)
    {
        double radius = diameter / 2;
        return Math.PI * radius * radius * level;
    }
    
    public static double FlowRate(double volumeStart, double volumeEnd, int minutes)
    {
        return (volumeEnd - volumeStart) / minutes;
    }
    
    public static string GetAlarmText(double value, double limit)
    {
        if (value > limit)
            return $"High: {value:F2} (Limit: {limit:F2})";
        else
            return "Normal";
    }
}

Step 4: Use Class in Expressions

In tag expressions:

csharp

@Script.Class.TankCalculations.CalculateVolume(@Tag.Tank1_Level, 10.5)

Step 5: Python Integration

1. Scripts → Settings
2. Enable Python
3. Create Python script:

python

import numpy as np
from datetime import datetime

def calculate_statistics(values):
    """Calculate statistical values"""
    arr = np.array(values)
    return {
        'mean': np.mean(arr),
        'std': np.std(arr),
        'max': np.max(arr),
        'min': np.min(arr)
    }

def predict_value(history, hours_ahead):
    """Simple linear prediction"""
    # Implementation here
    return predicted_value

# Set tag values
tags['Stats_Mean'] = calculate_statistics(history)['mean']

Step 6: Event-Driven Scripts

Create event handler:

csharp

// On tag change event
public void OnTemperatureChange()
{
    if (@Tag.Tank1_Temperature > @Tag.HighLimit)
    {
        @Tag.Alarm_Active = true;
        @Script.Class.Notifications.SendEmail(
            "operator@company.com",
            "High Temperature Alert",
            $"Tank 1: {@Tag.Tank1_Temperature}°C"
        );
    }
}

Bind to tag:

• Tag: Tank1_Temperature
• Event: OnValueChange
• Script: OnTemperatureChange

Step 7: Database Operations

Script for database logging:

csharp

public void LogProduction()
{
    string query = @"
        INSERT INTO ProductionLog 
        (Timestamp, Product, Quantity, Operator) 
        VALUES 
        (@time, @product, @qty, @user)";
    
    @Dataset.DB.SqlExecuteCommand(query,
        "@time", DateTime.Now,
        "@product", @Tag.Current_Product,
        "@qty", @Tag.Units_Produced,
        "@user", @Client.UserName
    );
}

Step 8: Test Scripts

1. Start Runtime with debugger
2. Set breakpoints in scripts
3. Monitor script execution:
   • Scripts → Monitor
   • Check execution time
   • View error messages

Best Practices

• Handle exceptions properly
• Log important events
• Optimize for performance
• Comment complex logic
• Test edge cases
• Use meaningful variable names

Next Steps

• [SQL Database Query] - Database integration
• [Reports Module] - Automated reporting
• [Create Dashboards] - Display calculations