Multi-factor Analysis Modeling Tool MFA - Root Cause Analysis - Yield Analysis - Virtual Measurement - Path Analysis - Custom Image - Multi-factor Analysis APP Application Solution - Gechuang Dongzhi

Pain Points

1. Industrial big data methods are complex and hard to use

Challenges include data complexity and numerous methods, deterring users;

2. Low data display efficiency, time-consuming reports

Auto-generate results with strong interpretability and readability;

3. Large and abnormal data volume

Users spend time on data format and anomaly handling, need process streamlining;

4. Unable to deploy models quickly

Accelerate deployment to save project costs

Core Advantages

  • Self-service Analysis
    Zero-code modeling for non-IT staff, improving data asset utilization
  • Visualization
    Visual modeling with clear, traceable analysis process
  • Real-time
    Real-time prediction monitoring, anomaly pre-warning for production
  • Model Self-learning and Self-updating
    Auto-update models with continuous data learning iteration

Application Scenarios

Root Cause Analysis

Data visualization exploration, dimensionality reduction for efficient mining and root cause analysis.

Yield Analysis

Precipitate engineer insights, summarize methods for automated yield analysis.

Virtual Measurement

Quantify and model know-how, monitor quality in real-time for lean production.

Path Analysis

Quickly locate abnormal sample paths, trace back equipment and parameters.

Custom Image

Quickly deploy industrial analysis images for rapid application and special scenarios.

Cases

Achieving Virtual Measurement for CVD Station with Dongzhi MFA

Customer: Semiconductor Panel Factory

Effect: Panel manufacturing has many complex stations. Engineers use MFA path analysis to quickly view NG product flows, identify abnormal paths via color, and locate faulty equipment.

Project Benefits: Anomaly time reduced 70%.

Data Governance Project

Customer: Semiconductor Display Enterprise

Effect: Enterprise faced data sharing challenges, low reusability, and quality gaps. Gechuang Dongzhi's data platform enabled assetization, value perception, and quality improvement through full-process monitoring and sharing.

Functional Modules

Root Cause Mining

Visual analysis + automated mining for flexible, efficient data analysis.

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