YMS良率提升管理系统-格创东智让工业更智慧--复制

Intelligent Yield Management System

The IYM system for industrial site management. With years of experience in industrial analysis, comprehensive analysis templates, advanced and rich data models, we help clients to tackle product defects accurately and efficiently from the aspects of yield monitoring

statistical analysis | big data intelligent analysis | automatic analysis | BI visualization | machine learning

Pain Points
User Value
Core Advantages
Application Scenarios
Cases
Functional Modules

Pain Points

Insufficient methods

In terms of solving yield problem and offering improvement strategy, there is a lack of data-based, systematic, and scientific analysis methods.

Low efficiency

Traditional methods and system tools are slow in data extraction and analysis, thus are inadequate in dealing with anomalies.

Poor flexibility

The solidification analysis can meet the requirements of conventional anomaly analysis, but cannot be used for efficient analysis of complex, multi-variant issues.

Low intelligence level

Descriptive tools such as visual reports, instead of intelligent applications, are used in forecasting and prevention.

User Value

Quick anomaly location

One-stop analysis has shortened analyzing time from days to hours or even minutes, therefore improving the efficiency considerably.

Improve product yield

Analytical models and predictive models can monitor the abnormalities in quality, prevent the flow of defective products to the next process, and improve the overall product yield.

Advanced process control

Integrating FDC, SPC, APC, etc., a comprehensive process control system is created to manage anomalies through a closed loop mechanism of interception, analysis and response.

Increase revenue

Employing yield rate analysis, production line monitoring and so on, to reduce production capacity Loss, save manpower and increase overall revenue.

Core Advantages

One stop analysis
A variety of determinate and indeterminate (A1+B1) analyzing methods such as integrated yield management, engineering data analysis, B analysis, Intelligent algorithm analysis and so on that can provide all-round solutions.
Autonomous modeling based on big data analysis
Simple and efficient DIY. Zero-code autonomous modeling based on machine learning, which works together with template analysis to adapt to different scenarios
Rich inventory of tools
Various control charts, reports, algorithm types, multi-dimensional analysis methods, visual analysis, customized templates with strong interactivity
Focus on industry
A variety of application and analysis templates such as precipitation root cause analysis, experimental analysis, path analysis, virtual measurement and so on that act from the engineer's perspective

Application Scenarios

Chip industry

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

Display panel industry

OLED panel manufacturing and assembly companies

PV industry

Crystallization and slicing, photovoltaic chip manufacturing, photovoltaic module companies

PCB and other industries

Printed circuit board industry and other industries that require integrated analysis of engineering data

Cases

GeTech iYMS helps analyze product anomaly

Client: Semiconductor Display Company
Outcome:
This semiconductor display company used to rely on manual monitoring to detect anomalies. Efficiency was low when multiple, complex and uncertain factors were involved, or when all equipment, parameters, eigenvalues were in need of analyzing. The company’s analyzing tools were inadequate.

GeTech employed Al+BigData to frame the analysis strategy for the engineers. Through Integrating MFA, KPC, Spotfre , an intelligent platform was built to solve yield problems by analyzing the correlation between product yield rate and time, machine, parameters and eigenvalues. The one-stop yield report enquiry and analysis system significantly improved efficiency and helped the engineers to locate anomaly promptly. The time spent on resolving anomalies has been reduced from days to hours. The users can analyze and do modeling promptly and independently. The extraction of comprehensive equipment parameters in any production process can be done with easy while the time spent on it has been shortened by ten times. The time spent on the one stop analysis report (generating+ machine + parameters) has been shorten by about 50 times, and the comprehensive yield increased by 3%, saving over 6 million per year.