Process predictive diagnosis and maintenance : UDM Insight
Prediction of abnormal symptoms based on control logic analysis: Using UXIM Platform
Trend analysis, predictive diagnosis, and parts life management by analyzing control characteristics
Pattern analysis of within-between control segment using x-AI and AutoML
Pattern analysis of within-between control segment using x-AI and AutoML
AS-IS
Analysis of external observations
- ·Only external observation data analysis: machine learning and AI
- ·Control segment characteristics are not considered (control characteristics are Black-Box)
- ·Failure to reflect characteristics of within-between control segment
TO-BE
x-AI & AutoML analysis of Internal dynamic control characteristics
- Internal control characteristics
- External Observations
- Control Segmentation
- X-AI pattern & AutoML related to internal control operation characteristics
- Selective use of necessary external observation data (cost reduction/purpose-oriented signal extraction possible)
- Pattern analysis for each control section is reflected in the x-AI model
Control Segment Features Analysis
Control Segment Patterning
Segment Adjacent Matrix
X-AI Modeling using AutoML
Part life management: U Insight
Development of parts life prediction system using x-AI and AutoML-based on E-PLAN standard Part Database
Reference: Hyundia Kia Motors, Dongyang Piston
Facility diagnosis through analysis of electric cylinder travel time
Reference: Dongyang Piston
Defect judgment through mold temperature analysis of casting machine
Reference: Pyeungwha Automotive
Predictive maintenance through injection molding condition analysis
R&D: UDM Analyzer (AutoML)
AI Quick Modeling Platform for Manufacturing data
