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Camgian Deploys Predictive Algorithms 
to Improve Process Controls

Downtime Mitigation for Global Pulp & Paper Company 


  • Critical equipment sensors: Essential sensors suffer frequent, unexpected failures

  • Real-time data loss: Lack of awareness hinders monitoring and proactive action

  • Delays and downtime: Unexpected stoppages disrupt production throughput

  • Maintenance concern: Shutting down entire line for sensor replacement not a viable option,
    creating further operational downtime


  • Use predictive analytics to overcome the limitations posed by sensor failures

  • Concept of “virtual signals” to predict measurements

  • Leverage real-time data from other sensors within the production process 

  • Predictive analytics algorithm that could accurately predict measurements of 
    broken sensors


  • Virtual sensors: Sustained production until planned maintenance, overcoming
    sensor failures

  • Reduced downtime: Bridging the gap between failures and quarterly planned repairs
    minimized production interruptions

  • Improved process control: Enabled proactive adjustments based on virtual sensor data

  • Enhanced efficiency: Big data and machine learning empowered a more productive and
    resilient operation

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