Deep Learning

Definition

Deep Learning is a machine learning technology that utilizes multi-layered neural networks to perform tasks such as classification, regression, and feature extraction. The term 'deep' originates from stacking multiple hidden layers to learn complex patterns, and can be implemented through supervised, semi-supervised, or unsupervised learning methods.

Applications in Manufacturing

Quality Inspection Automation

• Vision Inspection: Real-time detection of micro defects, scratches, and discoloration on product surfaces using CNN (Convolutional Neural Networks)
• Accuracy Enhancement: Achieving over 95% recognition rate for complex defect patterns compared to traditional rule-based inspection

Predictive Maintenance

• Analyzing equipment sensor data with time-series deep learning models to detect anomalies before failure
• Minimizing unplanned downtime and reducing maintenance costs

Process Optimization

• Learning nonlinear relationships among hundreds of process variables to derive optimal production conditions
• Yield improvement in complex manufacturing environments such as semiconductors and chemical processes

Key Points

When implementing deep learning in manufacturing, securing sufficient high-quality data is essential. Particularly, the imbalanced data problem—where defective samples are extremely rare compared to normal ones—must be addressed through data augmentation or transfer learning. Additionally, considering the black-box nature's interpretability limitations, it is recommended to incorporate Explainable AI (XAI) techniques in fields requiring quality certification.