Development and Simulation of an IoT-Enhanced Crushing Machine for Optimized Efficiency and Overload Protection

This research study focuses on designing a crushing machine capable of transforming materials into desired sizes and shapes while optimizing efficiency and ensuring protection from overload. Powered by high-capacity motors, the system employs a PIC-based Arduino controller for precise load monitoring and IoT integration. Controller selection is clarified through its real-time processing and connectivity capabilities. Accuracy is enhanced by utilizing advanced algorithms and high-performance sensors for load, vibration, and temperature tracking. Efficiency improvements include predictive maintenance, energy optimization, and refined operational strategies. Sensors are selected based on industrial requirements like sensitivity and reliability. Simulation and experimental validation demonstrate a strong correlation between operational parameters, achieving an accuracy margin within 10%, confirming the system's effectiveness for safe and efficient operation.