Sigmafine
Validates production information, verifies data quality, and helps produce clean, consistent, reliable data.
Data reconciliation and data validation
Information you can trust comes from data you can trust. Enterprise level systems assume the data they are provided is trustworthy, but if calibration errors, data from faulty transmitters, improperly entered measurements, or unmeasured process losses are entered into the ERP level, you could be making decisions based on bad data.
Sigmafine—the RtPM Platform’s data reconciliation and data validation package—uses a rigorous, mathematical approach to data reconciliation, generating information you can trust.
Linked to Sigmafine’s powerful reconciliation engine are comprehensive reporting and visualization tools, that let you report your results, create and update your models, and keep your plant information ready for action. Sigmafine’s end-user tools help you keep pace with your changing processes – ensuring that your information is always up-to-date.
As an integrated part of the RtPM Platform, Sigmafine’s calculation engine routes its reconciled data to the PI System Engine, making it available and instantly accessible to anyone or anything connected to the RtPM Platform. Your entire enterprise can now use Sigmafine to help make decisions based on a consistent set of trustworthy information.
Sigmafine uses all your available measurement data, taking full advantage of the power of your existing measurement redundancy, to create single set of accurate, consistent, reliable data. Sigmafine's powerful data reconciliation engine is based on the statistical least-squares method, which cross-checks measurement errors on all meter and gauge readings (based on a tolerance assigned to each measurement). Sigmafine is the only tool that can detect and identify the three most common errors in operation: gross error, random error, and bias error.
In a large operating area, data reconciliation is normally performed in isolation across the units within a single facility, then compiled for analysis. Rationalizing this information requires significant time and energy.
Sigmafine can perform a site-wide balance that takes into account information for the entire plant. The result is a consistent site and unit-by-unit balance, removing any underlying data conflict. Sigmafine's reconciliation algorithm is highly automated, stable, and based on rigorous statistics.
In addition to data reconciliation, Sigmafine is used by companies for mass balancing, component balancing, energy balancing, and unmeasured flow calculations.
Companies that have implemented Sigmafine as part of their RtPM are seeing considerable results including:
- Continuous improvement in plant monitoring and diagnosis
- Maintenance requirements predicted and prioritized
- Closed loop between actual data and production target
- Process losses monitored and identified
- Uncertainty margins narrowed
- Effects of random errors reduced or eliminated
- Errors and problems are detected and problems resolved faster
- Improved root-cause analysis
Data reconciliation and data validation
Information you can trust comes from data you can trust. Enterprise level systems assume the data they are provided is trustworthy, but if calibration errors, data from faulty transmitters, improperly entered measurements, or unmeasured process losses are entered into the ERP level, you could be making decisions based on bad data.
Sigmafine—the RtPM Platform’s data reconciliation and data validation package—uses a rigorous, mathematical approach to data reconciliation, generating information you can trust.
Linked to Sigmafine’s powerful reconciliation engine are comprehensive reporting and visualization tools, that let you report your results, create and update your models, and keep your plant information ready for action. Sigmafine’s end-user tools help you keep pace with your changing processes – ensuring that your information is always up-to-date.
As an integrated part of the RtPM Platform, Sigmafine’s calculation engine routes its reconciled data to the PI System Engine, making it available and instantly accessible to anyone or anything connected to the RtPM Platform. Your entire enterprise can now use Sigmafine to help make decisions based on a consistent set of trustworthy information.
Sigmafine uses all your available measurement data, taking full advantage of the power of your existing measurement redundancy, to create single set of accurate, consistent, reliable data. Sigmafine's powerful data reconciliation engine is based on the statistical least-squares method, which cross-checks measurement errors on all meter and gauge readings (based on a tolerance assigned to each measurement). Sigmafine is the only tool that can detect and identify the three most common errors in operation: gross error, random error, and bias error.
In a large operating area, data reconciliation is normally performed in isolation across the units within a single facility, then compiled for analysis. Rationalizing this information requires significant time and energy.
Sigmafine can perform a site-wide balance that takes into account information for the entire plant. The result is a consistent site and unit-by-unit balance, removing any underlying data conflict. Sigmafine's reconciliation algorithm is highly automated, stable, and based on rigorous statistics.
In addition to data reconciliation, Sigmafine is used by companies for mass balancing, component balancing, energy balancing, and unmeasured flow calculations.
Companies that have implemented Sigmafine as part of their RtPM are seeing considerable results including:
- Continuous improvement in plant monitoring and diagnosis
- Maintenance requirements predicted and prioritized
- Closed loop between actual data and production target
- Process losses monitored and identified
- Uncertainty margins narrowed
- Effects of random errors reduced or eliminated
- Errors and problems are detected and problems resolved faster
- Improved root-cause analysis