Camgian Deploys Predictive Algorithms
to Improve Process Controls
Downtime Mitigation for Global Pulp & Paper Company
Problem
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Critical equipment sensors: Essential sensors suffer frequent, unexpected failures
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Real-time data loss: Lack of awareness hinders monitoring and proactive action
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Delays and downtime: Unexpected stoppages disrupt production throughput
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Maintenance concern: Shutting down entire line for sensor replacement not a viable option,
creating further operational downtime
Solution
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Use predictive analytics to overcome the limitations posed by sensor failures
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Concept of “virtual signals” to predict measurements
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Leverage real-time data from other sensors within the production process
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Predictive analytics algorithm that could accurately predict measurements of
broken sensors
Conclusion
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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
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Enhanced efficiency: Big data and machine learning empowered a more productive and
resilient operation