Data Management Examples

Real-world production scenarios showing how to use Data Management for common industrial applications.

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Example 1: Production Counting by Time Dimension

Scenario: Track production output by minute, hour, and day from a cumulative counter.

Challenge

• Raw data: Cumulative counter that increments continuously
• Need: Net production per time period (minute/hour/day)
• Issue: Counter may reset to zero

Solution Architecture

Step 1: Create Raw Data Table

Table: Production_Raw

Field	Source	Formula
Cumulative_Count	Link to Tag: Counter	-
Net_Production	Formula	CHANGE([Cumulative_Count], 10000)

Trigger: Scheduled every 1 second

Explanation:

• CHANGE() function calculates the difference from the previous record
• If the counter resets (negative difference), it automatically adds 10000
• Result: Net production for each second

Step 2: Create Aggregation Tables

Table: Production_Hourly

Field	Source Field	Processing
Hour	Record Time	Group by Hour
Total_Parts	Net_Production	Sum

Table: Production_Daily

Field	Source Field	Processing
Day	Record Time	Group by Day
Total_Parts	Net_Production	Sum

Trigger: Real-time Update (or Scheduled daily at 00:01)

Step 3: Create Dashboard

Components:

1. Dropdown: Select time dimension (Hour/Day)
2. Table: Display production data
3. Time Range Filter: Select date range
4. Bar Chart: Visualize production trends

📷 [Screenshot: Production dashboard with time dimension selector]

Result: Operators can view production by hour or day, with automatic handling of counter resets.

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Example 2: Equipment Status Duration Tracking

Scenario: Track how long equipment is in each status (Running, Stopped, Fault) by hour, day, and shift.

Challenge

• Raw data: Equipment status code (0=Stopped, 1=Running, 2=Fault)
• Need: Duration in each status per time period
• Issue: Status changes frequently

Solution Architecture

Step 1: Create Raw Data Table

Table: Equipment_Status_Raw

Field	Source	Formula
Status	Link to Tag: Equipment_Status	-
Stopped_Duration	Formula	IF([Status] == 0, 1, 0)
Running_Duration	Formula	IF([Status] == 1, 1, 0)
Fault_Duration	Formula	IF([Status] == 2, 1, 0)

Trigger: Scheduled every 1 second

Explanation:

• Each status duration field returns 1 if the status matches, 0 otherwise
• When aggregated, the sum equals the total seconds in that status

Step 2: Create Aggregation Table

Table: Equipment_Status_Hourly

Field	Source Field	Processing
Hour	Record Time	Group by Hour
Stopped_Seconds	Stopped_Duration	Sum
Running_Seconds	Running_Duration	Sum
Fault_Seconds	Fault_Duration	Sum

Optional: Add fields to convert seconds to minutes:

Field	Formula
Stopped_Minutes	[Stopped_Seconds] / 60
Running_Minutes	[Running_Seconds] / 60
Fault_Minutes	[Fault_Seconds] / 60

Step 3: Create Dashboard

Components:

1. Stacked Bar Chart: Show duration by status and hour
2. Time Range Filter: Select date range
3. KPI Cards: Total duration for each status

📷 [Screenshot: Equipment status dashboard with stacked bar chart]

Result: Operators can see equipment utilization and identify downtime patterns.

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Example 3: Shift-Based Production Counting

Scenario: Track production by shift, including overnight shifts that span two calendar days.

Challenge

• Shift configuration: Day Shift (08:00-20:00), Night Shift (20:00-08:00)
• Need: Production count per shift
• Issue: Night shift spans two days (20:00 today → 08:00 tomorrow)

Solution Architecture

Step 1: Create Raw Data Table

Table: Production_Raw

Field	Source	Formula
Cumulative_Count	Link to Tag: Counter	-
Net_Production	Formula	CHANGE([Cumulative_Count], 10000)
Current_Shift	Link to Tag: System_Shift	-
Shift_Date	Link to Tag: System_ShiftDate	-

Trigger: Scheduled every 1 second

Explanation:

• System_Shift: System tag that returns current shift name
• System_ShiftDate: System tag that returns shift date (handles overnight shifts)

Step 2: Create Aggregation Table

Table: Production_By_Shift

Field	Source Field	Processing
Shift_Date	Shift_Date	Group by Day
Shift	Current_Shift	Group by Same Value
Total_Parts	Net_Production	Sum

Trigger: Scheduled daily at 00:01 (to handle overnight shifts)

⚠️ Important: Use scheduled trigger (not real-time) to ensure overnight shift data is complete.

Step 3: Create Dashboard

Components:

1. Table: Show production by shift and date
2. Time Range Filter: Select date range (filter by Shift_Date)
3. Bar Chart: Compare shifts

📷 [Screenshot: Shift production dashboard]

Result: Production is correctly attributed to shifts, even when shifts span two calendar days.

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Example 4: Alarm Count by Shift

Scenario: Count alarms by shift and date for analysis.

Challenge

• Data source: System alarm history table
• Need: Alarm count per shift
• Issue: Determine shift from alarm timestamp

Solution

Table: Alarm_Count_By_Shift

Source Table: Alarm Management - Historical Table (system table)

Field	Source Field	Formula	Processing
Alarm_Date	Trigger Time	-	Group by Day
Alarm_Hour	-	HOUR([Trigger Time])	-
Shift	-	IF([Alarm_Hour] < 14, "Day Shift", "Night Shift")	Group by Same Value
Alarm_Count	Alarm Name	-	Count

For Non-Integer Shift Times (e.g., 08:15-14:45):

Shift Formula:
IF(
  AND(
    OR([Alarm_Hour] > 8, AND([Alarm_Hour] == 8, MINUTE([Trigger Time]) >= 15)),
    OR([Alarm_Hour] < 14, AND([Alarm_Hour] == 14, MINUTE([Trigger Time]) <= 45))
  ),
  "Day Shift",
  "Night Shift"
)

For Overnight Shifts (e.g., 20:00-08:00):

Add field Is_Overnight:

[Alarm_Hour] <= 7

Adjust Alarm_Date:

IF([Is_Overnight] == FALSE, TODAY().AddDays(-1), [Trigger Time])

Dashboard: Stacked bar chart showing alarm count by shift and date.

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Best Practices from Examples

Data Collection

1. Use CHANGE() for Counters: Automatically handles counter resets
2. Record at Appropriate Frequency: Every second for fast processes, every minute for slow processes
3. Include Shift Information: Use system tags System_Shift and System_ShiftDate

Aggregation Strategy

1. Multi-Level Aggregation: Raw → Minute → Hour → Day → Month
2. Scheduled Triggers for Overnight Shifts: Use daily scheduled triggers instead of real-time
3. Group by Time First: Group by time dimension before grouping by category

Formula Techniques

1. Status Duration: Use IF([Status] == X, 1, 0) then sum
2. Shift Determination: Use HOUR() and MINUTE() functions with IF() logic
3. Counter Reset Handling: Use CHANGE() function with range parameter

Dashboard Design

1. Time Range Filters: Always provide date range selection
2. Multiple Views: Offer hourly, daily, and shift views
3. KPI Cards: Show key metrics at a glance
4. Stacked Charts: Use for comparing categories over time

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Next Steps

• Understanding Data Management - Review core concepts
• Creating Data Tables - Create your own tables
• Configuring Triggers and Formulas - Set up data collection
• Data Management Reference - Complete function library