IoT-Based Early Fault Detection System for Dust Collectors in Commutator Cutting Machinery

Abstract

This study aims to reduce machine downtime and increase production efficiency by developing an IoT-based early fault detection system for the dust collector of a commutator cutting machine at PT XYZ, an Indonesian automotive component manufacturer. The system addresses recurring issues related to insufficient suction pressure and copper powder buildup, which previously led to defective products and production interruptions. Using a prototype-based development approach, the system integrates real-time pressure monitoring, automatic tube switching, and visual–audio alerts to ensure stable operational performance. Sensor data are displayed locally on an LCD and remotely through a ThingsBoard dashboard, enabling rapid operator response. Validation results indicate fast data transmission with an average latency below 0.10 seconds, effectively preventing operational disruptions and reducing defective output. System implementation resulted in weekly production time savings of 30 minutes, the elimination of 100 defective units per month, and improved preventive maintenance supported by usage counters for filters and hoses. This work demonstrates the potential of IoT-based monitoring systems as scalable, data-driven, and cost-effective solutions for enhancing machine reliability and product quality.