Norsk
BosanskiAnalyzing Industrial Cyclones To Detect Defects
We digitized thirty industrial cyclones for Borregaard using just three cameras and true AI. The system accurately detects early structural defects and valve faults in real-time, significantly outperforming traditional mechanical PLC sensor installations.
The Challenge
Borregaard, a historic biochemical pioneer founded in 1889 with annual revenue approaching seven billion Norwegian kroner, produces sustainable alternatives to oil-based chemicals. Their facility relies on thirty large industrial cyclones and valve assemblies operating under demanding conditions.
Traditional manual inspections proved unreliable, while installing sixty individual physical sensors would create enormous hardware costs, complex wiring architectures, and ongoing maintenance expenses – all directly undermining the profitability of their eco-friendly manufacturing operation.
The Solution
We deployed a true AI computer vision system using just three high-resolution cameras to simultaneously monitor all thirty cyclones and valve handles. By digitizing physical conditions in real-time, our deep learning software tracks valve positions and structural anomalies across varying factory lighting conditions.
Trained on thousands of operational hours, the neural network detects microscopic airflow faults and mechanical irregularities before they escalate into catastrophic equipment failures or costly unplanned refinery stoppages.
Our Implementation Process
Audit & Testing
We thoroughly analyzed the factory layout to confirm that three strategically placed cameras could reliably capture all sixty data points across thirty industrial cyclones.
Hardware Setup
Three ruggedized industrial cameras were installed at carefully selected high-vantage positions, enabling full machinery coverage without complex plant rewiring.
True AI Training
Our proprietary neural network was trained on live operational video feeds to deeply understand normal cyclone behavior, valve positioning, and early anomaly signatures.
DCS System Link
Visual AI outputs were integrated directly into the main factory control room, delivering live equipment status updates to all floor operators and supervisors.
Proven Results
The Results & ROI
Massive Hardware Savings
Three cameras proved dramatically more cost-effective than purchasing, wiring, and maintaining sixty individual hardware sensors across the entire processing facility.
Early Error Detection
The AI vision system identifies microscopic airflow irregularities and structural faults at the earliest stage, preventing costly mechanical breakdowns.
Operator Confidence
Factory personnel now rely on the neural network more than manual observation, as the system has demonstrated consistently superior pattern recognition.
Green Profit Protection
By detecting resource leaks and mechanical inefficiencies early, the system safeguards Borregaard’s revenue stream while actively supporting their eco-friendly mission.
Trusted By Experts
What Our Industrial Partners Say
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