Detects oversized particles in real time, prevent blockages, overloads and damages in crushers before they happen.
Crusher breakdowns in cement plants are often caused by oversized rocks, improper material flow, and equipment overload. These issues result in unplanned downtime, higher maintenance costs, and reduced productivity. Implementing cement equipment predictive maintenance can help prevent these breakdowns by detecting problems early and ensuring smooth operations.
Large rocks (greater than 60 inches) on conveyor belts jam the primary crusher, causing significant cement plant downtime and becoming the biggest contributor to productivity loss
Blockages in crushers caused by oversized rocks can halt production, leading to increased downtime and reduced efficiency. These blockages require manual intervention to clear, disrupting operations and raising maintenance costs.
Undetected oversized rocks can cause blockages in crushers and conveyors, leading to equipment damage, increased maintenance costs, and reduced machinery lifespan.
Undetected oversized rocks disrupt the kiln's material flow, causing inefficient combustion and higher fuel consumption. Big rock detection ensures a consistent flow, optimizing fuel efficiency and reducing costs.
AI in cement equipment predictive maintenance helps identify potential issues before they cause costly breakdowns. By continuously monitoring equipment health and analyzing data, vision AI optimizes performance, reduces unplanned downtime, minimizes downtime in cement plants.
Achieve 15% reduction in conveyor stoppages due to accurate detection and estimation of large rocks.
Real-time big rock detection minimizes downtime in cement plants by preventing blockages and equipment damage.
Real-time crusher monitoring prevents blockages, reduces stress, minimizes wear, and ensures efficient, smooth operations.