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The Challenge
A cocoa processing plant needed to better understand and optimize its butter extraction cycles.
Two main issues stood in the way:
- Inability to define standard cycle durations or butter yields
- Lack of visibility into real-time hourly production, hindering performance tracking
Without clear KPIs, inefficiencies were hard to detect and production targets were difficult to benchmark.
The Approach
To tackle this, the team implemented a data-driven monitoring strategy centered around event-based validation and KPI tracking:
- Create a new derivative tag from butter production, to transform the output of every cycle into a continuous variable, with the aggregation functionality.
- Create a Value Based Search with all the production cycles during the period of interest. Add calculations such as integral of continuous flowrate, average pressure and recipe name.
- Export the results to Excel or analyze them within TrendMiner, with the event analytics option—finding correlations among aggregations or overlapping different cycles.
Key Insight
Analysis of cycle durations and valve behavior uncovered unnoticed performance variations—enabling tighter process control and cycle efficiency.
Responsive Image Gallery with Outline
Value Based Seach and added calculations to determine cocoa press performance
The Results
The Takeaway
By integrating real-time KPIs, event-driven alerts, and interactive dashboards, the site transformed its ability to:
- Detect low throughput early
- Maximize press performance
- Optimize cycle durations
- Reduce waste and inefficiencies
Want to uncover hidden inefficiencies in your batch process? Let’s explore how your data can power smarter production decisions and improve asset utilization.
The Challenge
A cocoa processing plant needed to better understand and optimize its butter extraction cycles.
Two main issues stood in the way:
- Inability to define standard cycle durations or butter yields
- Lack of visibility into real-time hourly production, hindering performance tracking
Without clear KPIs, inefficiencies were hard to detect and production targets were difficult to benchmark.
The Approach
To tackle this, the team implemented a data-driven monitoring strategy centered around event-based validation and KPI tracking:
- Create a new derivative tag from butter production, to transform the output of every cycle into a continuous variable, with the aggregation functionality.
- Create a Value Based Search with all the production cycles during the period of interest. Add calculations such as integral of continuous flowrate, average pressure and recipe name.
- Export the results to Excel or analyze them within TrendMiner, with the event analytics option—finding correlations among aggregations or overlapping different cycles.
Key Insight
Analysis of cycle durations and valve behavior uncovered unnoticed performance variations—enabling tighter process control and cycle efficiency.
Responsive Image Gallery with Outline
Value Based Seach and added calculations to determine cocoa press performance
The Results
The Takeaway
By integrating real-time KPIs, event-driven alerts, and interactive dashboards, the site transformed its ability to:
- Detect low throughput early
- Maximize press performance
- Optimize cycle durations
- Reduce waste and inefficiencies
Want to uncover hidden inefficiencies in your batch process? Let’s explore how your data can power smarter production decisions and improve asset utilization.
Access now
Share with a co-worker
The Challenge
A cocoa processing plant needed to better understand and optimize its butter extraction cycles.
Two main issues stood in the way:
- Inability to define standard cycle durations or butter yields
- Lack of visibility into real-time hourly production, hindering performance tracking
Without clear KPIs, inefficiencies were hard to detect and production targets were difficult to benchmark.
The Approach
To tackle this, the team implemented a data-driven monitoring strategy centered around event-based validation and KPI tracking:
- Create a new derivative tag from butter production, to transform the output of every cycle into a continuous variable, with the aggregation functionality.
- Create a Value Based Search with all the production cycles during the period of interest. Add calculations such as integral of continuous flowrate, average pressure and recipe name.
- Export the results to Excel or analyze them within TrendMiner, with the event analytics option—finding correlations among aggregations or overlapping different cycles.
Key Insight
Analysis of cycle durations and valve behavior uncovered unnoticed performance variations—enabling tighter process control and cycle efficiency.
Responsive Image Gallery with Outline
Value Based Seach and added calculations to determine cocoa press performance
The Results
The Takeaway
By integrating real-time KPIs, event-driven alerts, and interactive dashboards, the site transformed its ability to:
- Detect low throughput early
- Maximize press performance
- Optimize cycle durations
- Reduce waste and inefficiencies
Want to uncover hidden inefficiencies in your batch process? Let’s explore how your data can power smarter production decisions and improve asset utilization.
Access now
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