Artificial Neural Network (ANN)

Definition

Artificial Neural Network (ANN) is a machine learning computational model inspired by the structure and function of biological neurons in the human brain. It consists of interconnected nodes (neurons) organized in input, hidden, and output layers, with weighted connections that learn patterns from data to perform prediction or classification tasks.

Manufacturing Applications

Automated Quality Inspection

• Vision inspection: Detecting defects such as scratches, cracks, and foreign materials on product surfaces
• Measurement data analysis: Pass/fail judgment based on multivariate quality indicators like dimensions and weight

Predictive Maintenance

• Predicting equipment failure timing by analyzing sensor data (vibration, temperature, pressure)
• Early detection of anomalies in critical components like bearings and motors

Process Optimization

• Deriving optimal parameters for processes such as injection molding and heat treatment
• Improving efficiency through energy consumption pattern analysis

Key Points for Factory Implementation

• Data Quality: Accurate sensor data and sufficient training datasets are essential
• Real-time Processing: Inference time optimization to match production line speed
• Interpretability: Addressing black-box limitations for root cause analysis
• Edge Deployment: Applying lightweight models suitable for factory network environments