Smart Factory Integration with IIoT and Machine Learning for Optimized Manufacturing

Smart manufacturing has transformed through the IIoT and ML integration, which allows real-time monitoring, predictive analytics, and autonomous decisions. Traditional manufacturing systems go through significant difficulties because their predictive maintenance worked poorly, it could not detect defects effectively, and experienced high equipment downtime. A dual applied IIoT-ML structure that combines LSTM technology for predictive maintenance with CNN solutions for defect identification and reinforcement learning approaches for production improvement. The LSTM model reached 96.7% accuracy together with 2.1% false alarm reduction and the CNN model achieved 96.2% accuracy and better defect detection. The implementation of reinforcement learning optimization methods helped reduce downtime by 42.7% while decreasing energy use by 19.8%, which led to an OEE enhancement to 91.5%. The validation of the system occurred through AnyLogic digital simulation. The outcomes indicate that artificial intelligence-based manufacturing facilities increase operational efficiency while lowering expenses and elevating product quality, which leads to totally autonomous production systems.