AI for Water
Bringing closed-loop technology to the Waste Water treatment Industry.
- In the next decade, many WWT operations expect manpower shortages.
- Automated control of operating facilities is becoming more important every day.
- Our predictive and prescriptive solution enables a closed-loop system, similar to a self-driving car.
Using sophisticated tank monitors we are able to collect real-time data quality metrics to determine
- Current contaminant conditions
- BOD levels
- Oxygen levels
- Aging infrastructure
- Operator shortage due to retiring workforce
- Climate change
- Achieving EPA effluent standards
- Compliance controls
- Funding concerns
Packaging & Tissue
AI For Paper and Pulp Mills
Paper mills that implement ProcessMiner Cloud Platform realize clear benefits:
- Enhanced quality measurements with less error and variability
- Decreased operating costs by optimizing basis weight, chemistry usage and feedstock mixing
- Minimized process variability through step-wise process changes
- Improved quality consistency resulting in less downgrading
- Increased line speed without compromising quality
- Predictive “Soft Sensors” — ProcessMiner provides a real-time, mathematically driven measurement of paper quality metrics that cannot be delivered using any other method. Real-time predictions provide high-frequency data every 15 to 30 seconds. For the first time, papermakers can have a real-time quality profile of machine-direction properties for the entire length of the reel.
- Machine Learning — Due to the ever-changing environment of the papermaking process, it is crucial to continually update predictive analytics platforms. Using the machine learning capabilities built into the platform, OPTIX measurements remain robust and accurate in the face of changing machine conditions. Adaptive predictive models allow for more informed, on-the-fly process changes, rapid change detection, and process control optimization without requiring periodic model tuning.
- Prescriptive Recommendation Engine — Using deep learning and advanced data analytics methods, ProcessMiner prescribes real-time actionable insights for optimizing the manufacturing process. Operators can apply data-driven recommendations to maintain manufacturing conditions or target optimized machine efficiency.
- Model Diagnostics — Each ProcessMiner model comes equipped with a self-diagnostic prediction accuracy monitor. The platform evaluates the model accuracy using a metric related to the difference between the prediction and actual value of the quality measurement.
- Reduced Error
- Reduced Variability
- Improved Quality Consistency
- Adverse Event Detection
- Increased Production Volume
- Learning and Training