Wafer Processing Parameter Adjustment via Tool History Regression

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Solution Overview

Problem

Semiconductor manufacturers face challenges in controlling semiconductor device production due to ever-changing conditions within production tools, which affect critical dimensions and component positioning, leading to yield and performance issues.

Innovation Solution

A system and method that utilize a database to access and analyze tool history data, determining processing parameters based on regression models and constraints, including a slacked constraint and least absolute deviation objective function, to adjust for tool degradation and variability, ensuring consistent processing across different production tools.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If production tools are used continuously to process wafers, then productivity increases, but tool components wear and performance changes leading to manufacturing precision degradation

Engineering Contradiction:

Improvewafer processing throughputVSAvoidcritical dimension control

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The system implements feedback by continuously monitoring processing results and using regression models to determine adjusted processing parameters based on tool history data, ensuring that productivity gains do not compromise manufacturing precision

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically changes processing parameters based on regression analysis of tool history data, allowing the tool to maintain manufacturing precision throughout continuous operation despite component wear and performance drift

Inventive Principle:

Principle #35Parameter changes

2Productivity

If multiple production tools are deployed to increase capacity, then productivity improves, but variability in tool histories increases making control more difficult

Engineering Contradiction:

Improveproduction capacityVSAvoidtool history variability

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The regression-based control system serves as a universal solution that can be applied across multiple different production tools, normalizing their varied histories into a common framework that enables consistent control despite tool variability

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system introduces an intermediary layer of regression analysis and processing parameter adjustment that mediates between the varied tool histories and the required consistent output, eliminating the direct impact of tool variability on manufacturing precision

Inventive Principle:

Principle #24Intermediary (Mediator)

3Manufacturing precision

If processing parameters are adjusted frequently to maintain precision, then manufacturing precision is maintained, but process complexity and time for parameter determination increase

Engineering Contradiction:

Improvedevice feature controlVSAvoidparameter determination time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system performs preliminary action by building regression models from historical data in advance, so that when processing parameters need adjustment, the determination can be made quickly based on pre-established relationships rather than requiring complex real-time analysis

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS9523976B1Method and system for processing a semiconductor wafer using data associated with previously processed wafers

Publication Date: 2016.12.20 CYPRESS SEMICONDUCTOR CORP

AI summary

A method of processing a wafer in a production tool includes receiving a wafer at a process tool, the wafer associated with a wafer process history, acquiring data associated with wafers processed by the process tool and having the wafer process history, when the amount of acquired data is insufficient, acquiring additional data associated with wafers processed by the process tool and having a process history differing from the wafer process history by a single factor, when the amount of acquired data is sufficient, determining a process parameter using the acquired data, and processing the wafer with the production tool using the process parameter.