Intelligent diagnosis system for injection molding defection

In order to diagnose defects intelligently in the injection molding process, a model, which could quickly and accurately acquire defect diagnosis knowledge, is constructed to make decision for actual production. The model is based on the in-depth analysis of injection molding defects. Then rough set theory are used to construct a sample database and complete attribute reduction, rule self-extracting and self-learning. Finally potential relationships between defects symptoms and causes can be mined and some corresponding schemes can be applied in the injection molding with complex multi-mechanism effects to eliminate defects effectively.