eliminate conveyor breakdown

Conveyor Health Monitoring for Proactive Maintenance

Achieved 70% Reduction in downtime of conveyor failures with Ripik AI conveyor belt monitoring system. This ensured smoother operations, minimized downtime, and delivered significant cost savings.

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Problem Statement

Unmonitored conveyor systems lead to frequent breakdowns, unexpected downtime, and inefficient operations

Existing conveyor monitoring systems were inadequate, relying heavily on manual inspection, which was time-consuming, inconsistent, and unable to cover the entire belt effectively. Maintenance practices depended on constant human observation, often lacking attentiveness and leading to a reactive approach. This resulted in unexpected breakdowns and increased downtime.

Debris Damage to Conveyors

Bricks, metallic waste, and other debris cause severe damage to conveyors, chutes, and screens

Loose materials like bricks, scrap metal, and other debris often enter the material stream, causing repeated impact and abrasion on conveyors, chutes, and screens. This accelerates wear, increases the risk of equipment failure, and leads to frequent maintenance and unplanned downtime.

Undetected Wear and tear

Gradual deterioration, such as scratches and cracks in belts, often goes unnoticed until failure occurs

Gradual issues like scratches, cracks, and surface wear on conveyor belts often go unnoticed during routine checks, eventually leading to unexpected conveyor breakdowns and costly downtime.

Conveyor Sway

Conveyor sway leads to uneven wear, material spillage, and increased risk of breakdowns

Conveyor sway, often caused by misalignment, uneven loading, or worn-out rollers, leads to uneven belt wear, material spillage, and a higher risk of failures. If not corrected, it results in premature damage, safety risks, and costly downtime.

Pipe Conveyor Issues

Misalignment and prolonged non-opening of pipe conveyors can lead to unexpected shutdowns

Misalignment and prolonged non-opening of pipe conveyors disrupt material flow, leading to blockages, increased wear, and unexpected plant shutdowns.

Solution​

Ripik AI's uses a multi-camera system to prevent conveyor breakdowns with belt Monitoring

  • Specialized Hardware Conveyor monitoring uses specialized hardware and multi-camera systems designed to endure demanding belt operation conditions, ensuring reliable performance while continuously monitoring the belt surface for wear, misalignment, and anomalies.
  • Real-time Conveyor Belt Monitoring​ Real-time conveyor belt monitoring enables continuous tracking of belt conditions, instantly detecting wear, misalignment, and material spillage. Early identification of conveyor health issues allows for timely repairs, preventing further damage and minimizing unplanned downtime.
  • PLC Control on Anomalies Programmable Logic Controllers (PLCs) integrate with computer vision systems to enable real-time anomaly detection and trigger immediate corrective actions, such as stopping the conveyor belt to prevent damage.
  • Automated Anomaly Detection & Instant alerts AI detects anomalies on the conveyor belt and sends instant alert notifications via dashboards, WhatsApp, or emails, ensuring rapid response to potential issues.
  • Historical video feeds & insightful report The system archives of past conveyor belt footage conditions, allowing operators to review past events and identify patterns over time. Detailed reports provide actionable insights that support data-driven maintenance decisions and improve overall operational efficiency.
conveyor monitoring systems

Root Cause Analysis of conveyor anomaly detection

Impact and Accuracy Validation by End Users

conveyor monitoring systems

$300K+

Expected annual value generation

Over $300K in expected annual value generation was achieved by transitioning from manual inspection and verbal reporting to automated detection powered by real-time monitoring—enhancing accuracy, speed, and operational efficiency.

100+

Potential foreign object failures prevented in first 3 months

Over 100 potential foreign object failures were prevented in the first 3 months by shifting from delayed anomaly responses to instant notifications and proactive alerts.

70%

Reduction in downtime due to conveyor failures

Downtime from conveyor failures was reduced by 70% by shifting from reactive maintenance to predictive analytics, enabling proactive maintenance that automatically stops operations upon detecting foreign particles, preventing further damage.

Empowering leading global enterprises through our exceptional platform​

Empowering leading global enterprises through our exceptional platform​