Taiwan semiconductor manufacturing company, ltd. (20240376605). SYSTEM AND METHOD FOR DYNAMICALLY ADJUSTING THIN-FILM DEPOSITION PARAMETERS simplified abstract

SYSTEM AND METHOD FOR DYNAMICALLY ADJUSTING THIN-FILM DEPOSITION PARAMETERS

Organization Name

taiwan semiconductor manufacturing company, ltd.

Inventor(s)

Chung-Liang Cheng of Hsinchu (TW)

SYSTEM AND METHOD FOR DYNAMICALLY ADJUSTING THIN-FILM DEPOSITION PARAMETERS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240376605 titled 'SYSTEM AND METHOD FOR DYNAMICALLY ADJUSTING THIN-FILM DEPOSITION PARAMETERS

Simplified Explanation:

The thin-film deposition system described in the patent application utilizes a machine learning-based analysis model to optimize the deposition process on semiconductor wafers. By dynamically selecting process conditions based on target thin-film data, the system ensures the resulting thin films match the desired specifications.

• The system includes a machine learning-based analysis model.
• The analysis model dynamically selects process conditions for the deposition process.
• Static process conditions and target thin-film data are used to guide the selection of dynamic process conditions.
• The system aims to achieve predicted thin-film data that aligns with the target thin-film data.
• Both static and dynamic process conditions data are utilized for the thin-film deposition process.

Key Features and Innovation:

• Utilization of a machine learning-based analysis model for optimizing thin-film deposition.
• Dynamic selection of process conditions based on target thin-film data.
• Integration of static and dynamic process conditions data for accurate deposition results.

Potential Applications:

The technology can be applied in semiconductor manufacturing, solar cell production, and other industries requiring precise thin-film deposition processes.

Problems Solved:

The system addresses the challenge of achieving consistent and accurate thin-film deposition results by dynamically adjusting process conditions.

Benefits:

• Improved thin-film deposition accuracy and consistency.
• Enhanced efficiency in semiconductor manufacturing processes.
• Potential cost savings through optimized deposition processes.

Commercial Applications:

Optimizing thin-film deposition processes in semiconductor manufacturing can lead to increased production efficiency and higher quality end products, making the technology valuable for companies in the semiconductor industry.

Questions about Thin-Film Deposition System:

1. How does the machine learning-based analysis model contribute to the optimization of thin-film deposition processes? 2. What are the potential implications of using dynamic process conditions in thin-film deposition systems?

Frequently Updated Research:

Ongoing research in machine learning algorithms and semiconductor manufacturing processes may further enhance the capabilities of thin-film deposition systems like the one described in the patent application.

Original Abstract Submitted

a thin-film deposition system deposits thin films on semiconductor wafers. the thin-film deposition system includes a machine learning based analysis model. the analysis model dynamically selects process conditions for a next deposition process by receiving static process conditions and target thin-film data. the analysis model identifies dynamic process conditions data that, together with the static process conditions data, result in predicted thin-film data that matches the target thin-film data. the deposition system then uses the static and dynamic process conditions data for the next thin-film deposition process.