YMS Yield Improvement Management System - Intelligent Yield Management System - Yield Analysis System - GeChuang DongZhi -- Copy

Yield Management System (YMS)

Yield analysis system for industrial site management, with years of industrial analysis experience, using flexible and comprehensive analysis templates, advanced and rich data models, to help users accurately and efficiently solve yield-related issues.

Pain Points
User Value
Core Advantages
Application Scenarios
Case Studies
Functional Modules

Pain Points

Lack of Methods

Lack of systematic and scientific analysis methods starting from data dimensions to support solving yield issues and providing improvement strategies.

Low Analysis Efficiency

Traditional analysis methods and system tools have slow data extraction, long analysis times, and difficulty handling anomalies.

Poor Flexibility

Fixed analysis meets conventional anomaly analysis requirements but cannot efficiently analyze complex multi-factor issues.

Insufficient Intelligence

Mainly descriptive analysis like visual reports, with few intelligent applications for prediction and prevention.

User Value

Quickly Locate Anomalies

One-stop analysis, reducing analysis time from days to hours or minutes, greatly improving anomaly resolution efficiency.

Improve Product Yield

Using analysis models and prediction models to monitor quality anomalies, prevent abnormal products from flowing downstream, and improve overall product yield.

Advanced Process Control

Integrated with FDC, SPC, APC, etc., to form a comprehensive advanced process control system, achieving timely anomaly interception, analysis, and feedback management loop.

Enhance Enterprise Benefits

Through yield analysis, production line monitoring, etc., reduce capacity loss, save manpower, and improve overall benefits.

Core Advantages

One-Stop Analysis
Integrates yield management, engineering data analysis, BI analysis, intelligent algorithm analysis, and other fixed and unfixed (AI+BI) analysis methods to provide comprehensive solutions.
Big Data Analysis Self-Modeling
Simple and efficient DIY, zero-code machine learning self-modeling coexists with templated analysis to meet different application scenario needs.
Rich Tools
Diverse control charts, reports, algorithm types, multi-dimensional analysis methods, visual analysis, customizable analysis templates, strong interactivity.
Focus on Industry
Accumulates many application and analysis templates like root cause analysis, experimental analysis, path analysis, virtual measurement, close to engineers' perspective.

Application Scenarios

Chip Industry

Semiconductor material crystallization and slicing, chip manufacturing, packaging, design companies.

Panel Industry

Panel OLED manufacturing and assembly companies.

Photovoltaic Industry

Crystallization and slicing, photovoltaic chip manufacturing, photovoltaic module companies.

PCB and Other Industries

Printed circuit board industry and other industries requiring engineering data integration and analysis.

Case Studies

GETECH iYMS Intelligent Yield Management System helps achieve product anomaly analysis.

Client: Semiconductor display enterprise. Effect: A semiconductor display enterprise relied mostly on manual judgment and handling for anomalies; product anomaly factors are numerous and complex, when analyzing unknown multi-factors, analyzing all equipment, all parameters, and all feature values is inefficient, existing analysis tools cannot quickly analyze unknown multi-factors.

GETECH uses AI+BigData to solidify engineers' analysis methods, integrates MFA, KPC, Spotfire, etc., to build a unified yield intelligent platform, solving yield issues, analyzing correlations between product yield and various parameters like time, machines, parameters, feature values. One-stop yield report query and analysis, improving business efficiency; helping engineers quickly locate anomalies, improving anomaly resolution efficiency from days to hours; enabling user self-service rapid analysis modeling. Achieves convenient extraction of full process and equipment parameters, time reduced by 10 times; generates time+machine+parameter one-stop anomaly analysis reports, time reduced by about 50 times; overall yield improved by 3%; saves cost over 6 million yuan per year.