Semiconductor yield management system and method

Abstract

A system and method for yield management are disclosed wherein a data set containing one or more prediction variable values and one or more response variable values is input into the system. The system can process the input data set to remove prediction variables with missing values and data sets with missing values based on a tiered splitting method to maximize usage of all valid data points. The processed data can then be used to generate a model that may be a decision tree. The system can accept user input to modify the generated model. Once the model is complete, one or more statistical analysis tools can be used to analyze the data and generate a list of the key yield factors for the particular data set.

Description

BACKGROUND OF THE INVENTION [0001] 1. Field of the Invention [0002] The present invention relates generally to a system and method for managing a semiconductor manufacturing process and, more particularly, to a system and method for managing yield in a semiconductor fabrication process. [0003] 2. Description of the Prior Art [0004] The semiconductor manufacturing industry is continually evolving its fabrication processes and developing new processes to produce smaller and smaller geometries of the semiconductor devices being manufactured, because smaller devices typically generate less heat and operate at higher speeds than larger devices. Currently, a single integrated circuit chip may contain over one billion patterns. Consequently, semiconductor fabrication processes are extremely complex, and hundreds of processing steps may be involved. The occurrence of a mistake or small error at any of the process steps or tool specifications may cause lower yield in the final semiconductor ...

AI Technical Summary

Benefits of technology

[0011] One embodiment of the yield management system and method in accordance with the present invention provides many advantages over conventional yield management systems and techniques, which make the yield management system and method in accordance with the present invention more useful to semiconductor manufacturers. The system may be fully automated and is easy to use, so that no extra training is necessary to make use of the yield management system. In addition, the yield management system handles both continuous and categorical variables. The system also automatically handles missing data during a processing step that is optimized to consider data for all significant yield parameters. The system can rapidly search through hun

Problems solved by technology

Consequently, semiconductor fabrication processes are extremely complex, and hundreds of processing steps may be involved.

The occurrence of a mistake or small error at any of the process steps or tool specifications may cause lower yield in the final semiconductor product, where yield may be defined as the number of functional devices produced by the process as compared to the theoretical number of devices that could be produced assuming no bad devices.

In particular, the database technology has far outpaced the yield management analysis capability when using conventional statistical techniques to interpret and relate yield to major yield factors.

Many conventional yield management systems have a number of limitations and disadvantages which make them undesirable to the semiconductor manufacturing industry.

For example, conventional systems may require some manual processing which slows the analysis and makes the system susceptible to human error.

In addition, these conventional systems may not handle both continuous (e.g., temperature) and categorical (e.g., Lot 1, Lot 2, etc.) yield management variables.

Some conventional systems cannot ha

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