Limitations of SPC
Statistical Process Control (SPC) is a traditional quality management technique that detects process anomalies through control charts. However, it has limitations with multivariate processes and nonlinear patterns.
Problems with Traditional SPC
AI-SPC Fusion Architecture
Multivariate Anomaly Detection
Machine learning simultaneously analyzes dozens of process variables to detect anomaly patterns that traditional SPC misses.
Automatic Defect Root Cause Diagnosis
When an anomaly is detected, AI automatically analyzes which variables are the cause and provides corrective action guidance.
Automatic Process Parameter Correction
A prediction model calculates the probability of defect occurrence in real time and automatically adjusts process parameters.
Implementation Results
Conclusion
AI-SPC fusion is a new paradigm in manufacturing quality management. Realize quality innovation with POLYGLOTSOFT's AI platform and MES.