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This video explains how to use self-service analytics to compare a current production batch with an ideal "golden batch" fingerprint. This helps operators and engineers monitor processes in real-time, predict outcomes, and take corrective action sooner.
The Problem:
- During a batch cycle, it's difficult for operators to objectively assess if the current run will meet quality standards, finish on time, and stay within specifications.
- Manually analyzing thousands of historical batches to find the best-performing ones is time-consuming and challenging.
The Solution with TrendMiner:
The video demonstrates a step-by-step process using TrendMiner software to create and utilize a golden batch fingerprint.
- Finding the Best Batches:
- The user starts by searching through historical data to identify the best-performing batches.
- They use value-based search criteria. For example, they look for batches that were active for at least 60 minutes (indicating a complete run) and had a high product concentration (e.g., over 48 ppm), which signifies a good yield.
- They also sort these good batches by duration to find the ones that were completed in the shortest amount of time.
- Creating the Golden Batch Fingerprint:
- After identifying the top 10 best historical batches, the user overlays them to see the process trends.
- From these selected batches, a "golden fingerprint" is created. This fingerprint represents the ideal process profile, showing the acceptable range for key parameters like temperature, pressure, and concentration over time.
- Monitoring and Predicting in Real-Time:
- This golden fingerprint can be overlaid on a live, running batch.
- Using "Predictive Mode," the software compares the current batch's progress to the most similar historical batches in the database.
- This allows for a real-time visual comparison and predicts the likely outcome of the current batch, warning operators if it deviates from the ideal profile.
The Benefits:
- Early Corrective Action: Operators can identify potential problems early in the batch cycle and make adjustments to prevent a bad batch.
- Improved Consistency: New batches can be produced more consistently according to the proven efficiency of the golden fingerprint.
- Increased Efficiency: This process leads to improved Overall Equipment Effectiveness (OEE), reduced operational and maintenance costs, and minimized safety risks.
This video explains how to use self-service analytics to compare a current production batch with an ideal "golden batch" fingerprint. This helps operators and engineers monitor processes in real-time, predict outcomes, and take corrective action sooner.
The Problem:
- During a batch cycle, it's difficult for operators to objectively assess if the current run will meet quality standards, finish on time, and stay within specifications.
- Manually analyzing thousands of historical batches to find the best-performing ones is time-consuming and challenging.
The Solution with TrendMiner:
The video demonstrates a step-by-step process using TrendMiner software to create and utilize a golden batch fingerprint.
- Finding the Best Batches:
- The user starts by searching through historical data to identify the best-performing batches.
- They use value-based search criteria. For example, they look for batches that were active for at least 60 minutes (indicating a complete run) and had a high product concentration (e.g., over 48 ppm), which signifies a good yield.
- They also sort these good batches by duration to find the ones that were completed in the shortest amount of time.
- Creating the Golden Batch Fingerprint:
- After identifying the top 10 best historical batches, the user overlays them to see the process trends.
- From these selected batches, a "golden fingerprint" is created. This fingerprint represents the ideal process profile, showing the acceptable range for key parameters like temperature, pressure, and concentration over time.
- Monitoring and Predicting in Real-Time:
- This golden fingerprint can be overlaid on a live, running batch.
- Using "Predictive Mode," the software compares the current batch's progress to the most similar historical batches in the database.
- This allows for a real-time visual comparison and predicts the likely outcome of the current batch, warning operators if it deviates from the ideal profile.
The Benefits:
- Early Corrective Action: Operators can identify potential problems early in the batch cycle and make adjustments to prevent a bad batch.
- Improved Consistency: New batches can be produced more consistently according to the proven efficiency of the golden fingerprint.
- Increased Efficiency: This process leads to improved Overall Equipment Effectiveness (OEE), reduced operational and maintenance costs, and minimized safety risks.
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