Conmark Systems Inc.
Continuous Performance Improvements for the Pulp & Paper Industry        

Call +1-770-300-0224  or e-mail  sales@conmark.com                         


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Brown Stock Washing BLOX Causticizing Continuous Digester Batch Digester Dissolving Tank Lime Kiln Dry End Stock Prep Variable Reduction Wet End Process Mining
Agitators Actuators Chip Moisture CD Control Consistency Diff. Pressure Edge Guide Oil Flow PASVE Isolation valve Pressure Sample Valves Seal Water Flow Solid Content Turbidity Web Break Detector
Agitators Actuators Basis Weight CD Control Charge Chip Moisture Consistency Desktop Kappa Desktop Liquor Diff. Pressure Edge Guide Event Analyzer Liquor Analyzer Lime Kiln Microwave Basis Weight Oil Flow Paper Moisture PASVE Isolation valve Pressure ProcessMiner Property Predictor Portable Video Sample Valves Seal Water Flow Solid Content Turbidity Web Break Detector Wet End Scanner
CD Control Stock Prep Dry End Wet End
Brown Stock Washing BLOX Causticizing Continuous Digester Batch Digester Dissolving Tank Lime Kiln
Microwave Basis Weight Impregnated NonWoven

 

ProcessMiner®

Real-time Process Analyzer for Prediction or Fast Analysis of Root Cause of the Process Problems

The ProcessMiner® is a real-time root cause data analyzer that helps operators to detect process problems  even before they are creating process upsets. The Analyzer processes real-time data and compares it to the dataProcessMiner Dispaly for Wet End mining models developed from massive volumes of data collected by industrial databases such as PI System, OPC HDA, INSQL or by an internal SQL Server based high-speed servers.

The database systems acquire data from plants or processes via interfaces to automated control systems and other sources. These systems record data from thousands of these process ‘tags’, at specified intervals or by manual entry. Databases have build in history for almost every process condition, events or combination of them. This history can be utilized with data mining technology to model every potential combination of process problems or conditions when process was running in optimum state.

When the process deviates from optimum running state, operators can easily review process status on the DCS or on drive control panels and see which direction process is moving, what process variable is in motion, and what is the root cause or causes for predicted upset or event. Operator can easily monitor the process with Radar display and can quickly react to any changes or deviation from optimum process state.

In the papermaking industry, this provides tool for example of  predicting web breaks and other process related events and upsets or monitor state of the wet end or the lime kiln.

What is Data Mining
An information extraction activity, which goal is to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future events. Typical applications of data mining on commercial market place include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis.

Data Mining=Information Mining



Features:

  • Graphical user interface
  • Automatic ranking of high variability tags
  • Quick to install
  • Database-driven analytical tools
  • Ability to e-mail results
  • Based on industry standards ‘Good run’ versus ‘bad run’ comparison
  • User-selectable ranking criteria

Benefits:

  • Easy to understand and to use
  • Immediate analysis available
  • Quick payback, minimum disruption to operations
  • Facilitates process improvements
  • Improves knowledge-sharing
  • Integrates with existing systems
  • Easy to check the effect of changes
  • Can deal with gradual process changes

Fast Payback:

The ProcessMiner® helps operations staff to quickly react to potential process failures such as web breaks, generator trips and other process events, reducing the likelihood of lost production

  • Minimizes lost production
  • Saves labor
  • Increases the runnability of the Paper Machine
  • Avoids secondary failures due to misdiagnosis
  • Leads to rapid process improvement