Classification (Statistical Classification)
Last updated 2026.02.13Definition
Classification is a statistical machine learning technique that assigns input data to one of predefined categories (classes). When classification is performed by a computer, statistical methods are normally used to develop the algorithm, learning patterns from historical data to predict the category of new data.
Applications in Manufacturing
Quality Inspection Automation
- Defect Detection: Automatically classify products as pass/fail
- Defect Type Classification: Categorize defect types such as scratches, cracks, and discoloration
- Vision Inspection: Detect visual anomalies by analyzing camera images
Equipment Management
- Failure Type Classification: Diagnose failure causes from sensor data
- Predictive Maintenance: Classify equipment status into normal/caution/critical for proactive maintenance planning
Process Optimization
- Process State Monitoring: Determine process stability from temperature, pressure, and vibration data
- Raw Material Grading: Automatically classify quality grades of incoming materials
Key Points
Selection of classification models depends on data characteristics and field requirements. Various algorithms such as decision trees, random forests, SVM, and neural networks are utilized. In manufacturing environments, not only model accuracy but also interpretability and real-time processing speed are crucial selection criteria. Particularly in defect detection, balancing false positives and false negatives directly impacts productivity and quality assurance.